Learn more advanced front-end and full-stack development at: https://www.fullstackacademy.com

Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interactions between computers and human language. In this Natural Language Processing Tutorial, we give an overview of NLP and its uses, before diving into the Natural library for Node.js and how easily you can use it for inflectors, string distance, classifications with machine learning, and term frequency using various algorithms.

Watch this video to learn:

– What is NLP
– Natural Language Processing use cases
– How to use the Natural library in Node.js

🔥 Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training
This Edureka Machine Learning Full Course video will help you understand and learn Machine Learning Algorithms in detail. This Machine Learning Tutorial is ideal for both beginners as well as professionals who want to master Machine Learning Algorithms. Below are the topics covered in this Machine Learning Tutorial for Beginners video:
00:00 Introduction
2:47 What is Machine Learning?
4:08 AI vs ML vs Deep Learning
5:43 How does Machine Learning works?
6:18 Types of Machine Learning
6:43 Supervised Learning
8:38 Supervised Learning Examples
11:49 Unsupervised Learning
13:54 Unsupervised Learning Examples
16:09 Reinforcement Learning
18:39 Reinforcement Learning Examples
19:34 AI vs Machine Learning vs Deep Learning
22:09 Examples of AI
23:39 Examples of Machine Learning
25:04 What is Deep Learning?
25:54 Example of Deep Learning
27:29 Machine Learning vs Deep Learning
33:49 Jupyter Notebook Tutorial
34:49 Installation
50:24 Machine Learning Tutorial
51:04 Classification Algorithm
51:39 Anomaly Detection Algorithm
52:14 Clustering Algorithm
53:34 Regression Algorithm
54:14 Demo: Iris Dataset
1:12:11 Stats & Probability for Machine Learning
1:16:16 Categories of Data
1:16:36 Qualitative Data
1:17:51 Quantitative Data
1:20:55 What is Statistics?
1:23:25 Statistics Terminologies
1:24:30 Sampling Techniques
1:27:15 Random Sampling
1:28:05 Systematic Sampling
1:28:35 Stratified Sampling
1:29:35 Types of Statistics
1:32:21 Descriptive Statistics
1:37:36 Measures of Spread
1:44:01 Information Gain & Entropy
1:56:08 Confusion Matrix
2:00:53 Probability
2:03:19 Probability Terminologies
2:04:55 Types of Events
2:05:35 Probability of Distribution
2:10:45 Types of Probability
2:11:10 Marginal Probability
2:11:40 Joint Probability
2:12:35 Conditional Probability
2:13:30 Use-Case
2:17:25 Bayes Theorem
2:23:40 Inferential Statistics
2:24:00 Point Estimation
2:26:50 Interval Estimate
2:30:10 Margin of Error
2:34:20 Hypothesis Testing
2:41:25 Supervised Learning Algorithms
2:42:40 Regression
2:44:05 Linear vs Logistic Regression
2:49:55 Understanding Linear Regression Algorithm
3:11:10 Logistic Regression Curve
3:18:34 Titanic Data Analysis
3:58:39 Decision Tree
3:58:59 what is Classification?
4:01:24 Types of Classification
4:08:35 Decision Tree
4:14:20 Decision Tree Terminologies
4:18:05 Entropy
4:44:05 Credit Risk Detection Use-case
4:51:45 Random Forest
5:00:40 Random Forest Use-Cases
5:04:29 Random Forest Algorithm
5:16:44 KNN Algorithm
5:20:09 KNN Algorithm Working
5:27:24 KNN Demo
5:35:05 Naive Bayes
5:40:55 Naive Bayes Working
5:44:25Industrial Use of Naive Bayes
5:50:25 Types of Naive Bayes
5:51:25 Steps involved in Naive Bayes
5:52:05 PIMA Diabetic Test Use Case
6:04:55 Support Vector Machine
6:10:20 Non-Linear SVM
6:12:05 SVM Use-case
6:13:30 k Means Clustering & Association Rule Mining
6:16:33 Types of Clustering
6:17:34 K-Means Clustering
6:17:59 K-Means Working
6:21:54 Pros & Cons of K-Means Clustering
6:23:44 K-Means Demo
6:28:44 Hierarchical Clustering
6:31:14 Association Rule Mining
6:34:04 Apriori Algorithm
6:39:19 Apriori Algorithm Demo
6:43:29 Reinforcement Learning
6:46:39 Reinforcement Learning: Counter-Strike Example
6:53:59 Markov’s Decision Process
6:58:04 Q-Learning
7:02:39 The Bellman Equation
7:12:14 Transitioning to Q-Learning
7:17:29 Implementing Q-Learning
7:23:33 Machine Learning Projects
7:38:53 Who is a ML Engineer?
7:39:28 ML Engineer Job Trends
7:40:43 ML Engineer Salary Trends
7:42:33 ML Engineer Skills
7:44:08 ML Engineer Job Description
7:45:53 ML Engineer Resume
7:54:48 Machine Learning Interview Questions

———–Edureka Machine Learning Training ————

🔵 Machine Learning Course using Python: http://bit.ly/38BaJco

🔵 Machine Learning Engineer Masters Program: http://bit.ly/2UYS46r

🔵Python Masters Program: https://bit.ly/3cVibjY

🔵 Python Programming Training: http://bit.ly/38ykZCg

🔵 Data Scientist Masters Program: http://bit.ly/31ZsWOn

PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai

Post Graduate Certification in Data Science with IIT Guwahati – https://www.edureka.co/post-graduate/data-science-program
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)

——————————————————————————————————–

Instagram: https://www.instagram.com/edureka_learning
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

———————————————————————————————————-

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Artificial intelligence 25 Predicate Logic In ai or predicate logic in artificial intelligence.
predicate logic is different from prepositional logic as predicate logic deals with relation and real world entity unlike prepositional logic which is based on true or false
predicate logic deals with 3 world entities known as
predicate object, predicate function predicate relation.
predicate logic has ability to represent facts about object
predicate logic enables to represent law and facts from real world entity
predicate syntax follow object , relation and function. this video is about predicate logic in artificial intelligence

Natural language processing is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze large amounts of natural language data. #ArtificialIntelligence #NaturalLanguageProcessing

Follow me on Instagram 👉 https://www.instagram.com/ngnieredteacher/
Visit my Profile 👉 https://www.linkedin.com/in/reng99/
Support my work on Patreon 👉 https://www.patreon.com/ranjiraj

Face Detection for NET using EMGU.CV in C# .NET Windows Forms Application.

Website: http://foxlearn.com

face recognition c# emgu cv example
face recognition in c# using emgu cv
face recognition in c# windows application
c# face matching
emgu cv dll
emgu cv image recognition library
face detection in c# source code
face recognition c# github
emgu cv image recognition library
emgu cv download
face detection and recognition in c# using emgu cv 3.0 opencv wrapper
c# solutions face detection recognition system

Program your computer to LISTEN to YOU + RESPOND! [C# Programming] It is extremely easy to do, and in a few minutes, you’ll be asking your computer to do tasks for you!

My Equipment:
Behringer UMC22: https://amzn.to/30hrpWj
Audio-Technica AT2020: https://amzn.to/31EYZSt

Link to have all English words in grammar without typing them: http://youtu.be/gEBWsLSRVL4
Program Code: http://goo.gl/zhMFV [Google Drive .txt file]
[If you just copy the code, remember to add the reference for speech recognition by going to the ‘references’ drop down area in the Solution Explorer, right-click on it, and click ‘Add Reference’. Click ‘.NET’ at the top, or ‘Framework’ on v.2012 and scroll down until you see ‘System.Speech’. Check the check box, and your copied code will now work!]

In this video I am going to show you how to setup a voice recognition system which allows your users to perform tasks using just their voice.

Follow me on Twitter:
http://www.twitter.com/JohnnyMansonIC

Watch the MoonLight OS Release Video:
https://www.youtube.com/watch?v=vyo6BJyakx4

Download MoonLight OS:
http://www.intracode.org/products.html

Intro Song:
Robot Koch – Hard To Find
http://www.amazon.com/Hard-To-Find/dp/B002TXL8K2-
https://www.youtube.com/watch?v=g9zFzKA2r5o
http://www.projectmooncircle.com
https://soundcloud.com/robot-koch
http://www.robotsdontsleep.com

Machine Learning Tutorial at Imperial College London:
Bayesian Nonparametrics and Priors over Functions
Carl Henrik Ek (University of Bristol)
November 22, 2017

Welcome to………
Db Foundation Bangladesh (DFB)

In this video, I show how to set up Google assistant on any Android phoen.
You know, Google assistance is a most powerful Artificial Intelligent.
You can ask any question to Google assistant, its will answer you accurately of your any kind of question.

All information of the world know google assistant.
Google really lunched this helpful way for Android user.
So we should to thanks Google Inc.

Process to set up:
First update ‘Google Play Service (beta)’ from play store.
Now Clear All Data from Google play service and google service from Setting/ App mmanagement/ Find App Google Play service & Google/Manage space /Clear All data.
Select Default US English language form setting.

Now go back home,
Press and hold Home button of your phone.
You are done. Now enjoy…
Thank you…

Here you can learn a lot about ICT/IT, education & more thing.
We are offering you to learn something about ICT from our channel, because if you are illiterate on ICT, You may be deceived in online.
We don’t post any fake, unworkable, fraud related video in our channel.
Our All video is very important to promote ICT knowledge.

We are trying to gain love & better response from our subscribers & we always given priority to our subscribers satisfaction.
Our objectives:
►Promoting skill on ICT/IT.
►Speaking against online Rogue.
►Reducing superstition.
►Enhancing mobility of education.

Subscribe Our Channel: https://www.youtube.com/c/dbfoundationbangladesh

Contact with us through:
►Personal Contact: https://www.facebook.com/saem.ibrahim
►Facebook Page: https://www.facebook.com/dbfoundation.bd
►E-mail: dbfoundation.bd@gmail.com

Thanks for watching our video……

Hey Guys,
Hope you enjoying my AI tutorials using Keras and Tensorflow.

This is the video for facial emotion recognition using CNN.
Transfer learning is the best way to perform such a complicated task.
For this task, we will classify the emotions from the frame coming directly through your webcam or any external live camera.

This is a realtime emotion detection easy tutorial using python and Keras.

You can use this video as realtime emotion detection using python.

Please do share and subscribe for more interesting videos.

Dataset :- https://drive.google.com/open?id=1E66iZdNz021aUZGsZjtc3EUu3NqAaIq3

Source Code :- https://github.com/code-by-dt/emotion_detection

Facial Landmark Detection OpenCV Too Easy Tutorial https://youtu.be/16bzzVaqKCk

Computer Vision Programs :- https://www.youtube.com/playlist?list=PLgNUGWgXIL4pWASWqSdAvYupEocaktF2D

—————PROGRAMMERS SECTION——————–

➤Follow Me On Git Hub🐈:-https://github.com/code-by-dt
➤Follow Me On HackerRank:-https://www.hackerrank.com/code_by_dt
➤Join me on Slack:- https://join.slack.com/t/codebydt/shared_invite/enQtNzcwMjU0Nzg0MzI0LWYwOGM2MDI4NjQxYmFiMDlhYzc2YjEwYjc1MTc0NmIxNzQzZWU3ZmJmMDcyNmQyMDVjYjI3YWRjOWEzNDdhMDE

Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favour of fair use.

▬▬★▬Social Media▬▬★▬▬

🌐Facebook➤ https://www.facebook.com/dttechupdates
🌐Twitter➤ https://www.twitter.com/dttechupdates
🌐Instagram➤ https://www.instagram.com/dttechupdates

▬▬★▬Google Plus (G+)▬★▬▬

Community➤https://plus.google.com/u/0/communities/104307297318953975855

Don’t forget to:-

1. Like 👍
2. Subscribe
3. Share ❤

This episode is all about taking your AE2 game to the next level. We’ll cover Quantum Link chambers which allow you to transmit your network wirelessly over an infinite distance, even cross-dimensionally! We’ll also dabble in a little bit of sub-networking but the majority of the video is devoted to the power of P2P tunnels which allow for some seriously compact setups.

[QUICK JUMP]
0:15 – Quantum Link Chambers
2:52 – P2P Tunnels (all variants except ME)
7:55 – P2p Tunnels – ME
14:16 – Sub Networks
18:13 – Visualizing P2P & Compact setups

[More AE2 Tutorials]
AE2 – EP01 – A Beginner’s Guide – https://youtu.be/AjrMS4EhBEU
AE2 – EP02 – Your First Network – https://youtu.be/sD2GknUv1cM
AE2 – EP03 – Autocrafting – https://youtu.be/os5EYegEudE

P2P Conversion Recipes:
http://ae-mod.info/P2P-Tunnel/

[MODPACK & MOD VERSION]
DW20 1.12
Applied Energistics 2 rv5-stable-4

ABOUT US]
We are TheMindCrafters and we make tutorials/LPs/and Spotlights on our favorite (and guest requested) Minecraft mods, blocks, and modpacks
Our Site – http://theMindCrafters.com
Live Chat – http://theMindCrafters.com/#chat

( **Natural Language Processing Using Python: – https://www.edureka.co/python-natural-language-processing-course ** )
This video will provide you with a detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this video:

0:46 – Introduction to Big Data
1:45 – What is Text Mining?
2:09- What is NLP?
3:48 – Introduction to Stemming
8:37 – Introduction to Lemmatization
10:03 – Applications of Stemming & Lemmatization
11:04 – Difference between stemming & Lemmatization

Subscribe to our channel to get video updates. Hit the subscribe button above https://goo.gl/6ohpTV

———————————————————————————————–
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
———————————————————————————————–

– – – – – – – – – – – – – –

How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

– – – – – – – – – – – – – –

About the Course

Edureka’s Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed.

This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience.

————————–

Who Should go for this course ?

Edureka’s NLP Training is a good fit for the below professionals:
From a college student having exposure to programming to a technical architect/lead in an organisation
Developers aspiring to be a ‘Data Scientist’
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Text Mining Techniques
‘Python’ professionals who want to design automatic predictive models on text data
“This is apt for everyone”

———————————

Why Learn Natural Language Processing or NLP?

Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users.

NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data.

———————————

For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free).

** Edureka RPA Training (Use Code: YOUTUBE20) : https://www.edureka.co/robotic-process-automation-certification-courses **
This Edureka Robotic Process Automation Full Course video will help you understand and learn RPA in detail. This RPA Tutorial is ideal for both beginners as well as professionals who want to master RPA tools such as UiPath & Automation Anywhere. Below are the topics covered in this RPA tutorial video:
1:56 Introduction to RPA
2:26 Why RPA?
8:46 What is RPA?
10:16 RPA Tools
10:26 RPA Lifecycle
11:01 Discovery Phase
14:36 Solution Design Phase
17:35 Development Phase
18:16 UAT
18:51 Deployment Phase
19:21 Execute Bots
22:31 Introduction to UiPath
23:01 UiPath Studio
23:11 UiPath Installation
25:36 UiPath Studio Projects
29:46 UiPath Studio Ribbon Components
40:01 UiPath Studio Activity Pane Components
42:41 UIPath Studio Properties Pane
43:16 UiPath Studio Output Pane
49:46 UiPath RPA Architecture
50:11 UiPath Platform Components
50:21 UiPath Studio
52:21 UiPath Orchestrator
55:21 UiPath Architecture
58:11 Variables, Data Types & Activities in UiPath
1:03:11 Types of Variables
1:08:56 Data Types
1:10:16 Activities
1:12:16 Message Box
1:15:51 Write CSV Activity
1:18:56 If Activity
1:21:51 For Each Activity
1:24:41 While Activity
1:27:31 Do While Activity
1:29:06 Switch Activity
1:31:26 Automations in UiPath
1:31:31 Why Excel Automation?
1:32:21 Installing Excel Activities in UiPath Studio
1:33:46 Demo; Automating the Filling of a Form
1:48:06 UiPath Selectors
1:48:51 What are Selectors?
1:51:16 Why do we need Selectors in UiPAth?
1:53:26 Demo: Selectors in UiPath
2:21:51 UiPath Web Automation
2:24:01 Hands-on: Web Scraping of Google Contacts
2:24:01 Hands-on: Extracting Data From E-Commerce Website
2:46:26 UiPath PDF Automation
2:48:01 Types of PDF Activities
2:49:43 Demo: Extracting Large Texts
3:03:08 Demo: Extracting Specific Element
3:11:58 UiPath Email Automation
3:15:03 Demo: UiPath Email Automation
3:45:53 UiPath Citrix Automation
3:46:18 Automating Virtual Machine
3:48:53 Why Citrix Automation?
3:49:53 Hands-on: Simple Desktop Application
3:59:18 Debugging & Error Handling in UiPath
3:59:43 Debugging in UiPath
4:17:33 Exception Handling in UiPath
4:22:08 UiPath Tips & Tricks
4:29:28 Orchestrator in UiPath
4:33:38 UiPath Orchestrator Community Edition
5:06:23 UiPath ReFramework
5:06:38 Why Re-Framework?
5:08:48 What is Re-Framework?
5:12:38 How to use Re-Framework?
5:14:43 Re-Framework Architecture
5:18:11 INIT State
5:32:01 Get Transaction Data State
5:39:13 Process Transaction State
5:54:28 End Process State
5:58:18 RPA & UiPath Interview Questions
7:11:50 Introduction to Automation Anywhere
7:11:55 What is Automation Anywhere?
7:12:55 Automation Anywhere Architecture
7:15:30 Products of Automation Anywhere
7:23:50 Industries Using Automation Anywhere
7:28:05 Automation Anywhere Installation
7:44:50 Install & Setup Client
7:49:00 Control Room & Bots
7:49:35 Automation Anywhere Architecture
7:52:40 Control Room Components
8:02:10 Hands-on
8:06:30 Automation Anywhere Bots
8:08:00 Types of Automation Anywhere Bots
8:08:20 Task Bots
8:10:50 Meta Bots
8:25:20 IQ Bots
8:27:08 Products of Automation Anywhere
8:28:13 Automation Anywhere Examples
8:28:53 Windows Action
8:33:08 Mouse Clicks
8:35:58 String Operations
8:41:23 Files & Folders
8:44:38 Web Recorders
8:49:34 OCR
8:51:49 Key Strokes
8:53:14 REST Web Services
8:55:39 Excel Automation
9:04:14 PDF Automation
9:15:24 Automation Anywhere Interview Questions
9:17:04 Basic Questions
9:33:19 Tool-based Questions
9:57:04 Scenario-based Questions

——————————————————————————————————–

Instagram: https://www.instagram.com/edureka_learning
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

———————————————————————————————————-

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Laws for converting Preposition logic statement into more complex statements for solutions of given problem by using resolution which uses negotiation of a given statement

github url :https://github.com/krishnaik06/Google-Cloud-Platform-Deployment

Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more
https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join

Please do subscribe my other channel too
https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw

Connect with me here:

Twitter: https://twitter.com/Krishnaik06

Facebook: https://www.facebook.com/krishnaik06

instagram: https://www.instagram.com/krishnaik06

➡In this artificial intelligence course you will learn end to end about ai and it’s vast domain. So this artificial intelligence tutorial is an exhaustive tutorial for you to get started with ai.
🔥Intellipaat artificial intelligence course: https://intellipaat.com/artificial-intelligence-masters-training-course/
📕 Read complete artificial intelligence tutorial here: https://intellipaat.com/blog/tutorial/artificial-intelligence-tutorial/
#artificialintelligencetutorial #artificialintelligencecourse #artificialintelligence #aitutorialforbeginners #aicourse #learnartificialintelligence #aicourse #intellipaat

📌 Do subscribe to Intellipaat channel & get regular updates on technological videos: http://bit.ly/Intellipaat

🔗 Watch artificial intelligence video tutorials here: https://goo.gl/gyf2g3

📰Interested to learn artificial intelligence still more? Please check similar what is artificial intelligence blog here: https://intellipaat.com/blog/what-is-artificial-intelligence/

Are you looking for something more? Enroll in our artificial intelligence course and become a certified ai professional (https://intellipaat.com/artificial-intelligence-masters-training-course/). It is a 143 hrs instructor led ai for everyone training provided by Intellipaat which is completely aligned with industry standards and certification bodies.

If you’ve enjoyed this video, Like us and Subscribe to our channel for more similar videos and free tutorials.
Got any questions? Ask us in the comment section below.

—————————-
Intellipaat Edge
1. 24*7 Life time Access & Support
2. Flexible Class Schedule
3. Job Assistance
4. Mentors with +14 yrs
5. Industry Oriented Course ware
6. Life time free Course Upgrade
——————————

Why Artificial Intelligence is important?

Artificial Intelligence is taking over each and every industry domain. Machine Learning and especially Deep Learning are the most important aspects of Artificial Intelligence that are being deployed everywhere from search engines to online movie recommendations. Taking the Intellipaat deep learning training & Artificial Intelligence Course can help professionals to build a solid career in a rising technology domain and get the best jobs in top organizations.

Why should you opt for a Artificial Intelligence career?

If you want to fast-track your career then you should strongly consider Artificial Intelligence. The reason for this is that it is one of the fastest growing technology. There is a huge demand for professionals in Artificial Intelligence. The salaries for A.I. Professionals is fantastic.There is a huge growth opportunity in this domain as well. Hence this Intellipaat Artificial Intelligence tutorial is your stepping stone to a successful career!
——————————
For more Information:
Please write us to sales@intellipaat.com, or call us at: +91- 7847955955

Website: https://intellipaat.com/artificial-intelligence-masters-training-course/

Facebook: https://www.facebook.com/intellipaatonline

Telegram: https://t.me/s/Learn_with_Intellipaat

Instagram: https://www.instagram.com/intellipaat

LinkedIn: https://www.linkedin.com/in/intellipaat/

Twitter: https://twitter.com/Intellipaat

To begin, what is regression in terms of us using it with machine learning? The goal is to take continuous data, find the equation that best fits the data, and be able forecast out a specific value. With simple linear regression, you are just simply doing this by creating a best fit line.

From here, we can use the equation of that line to forecast out into the future, where the ‘date’ is the x-axis, what the price will be.

A popular use with regression is to predict stock prices. This is done because we are considering the fluidity of price over time, and attempting to forecast the next fluid price in the future using a continuous dataset.

Regression is a form of supervised machine learning, which is where the scientist teaches the machine by showing it features and then showing it was the correct answer is, over and over, to teach the machine. Once the machine is taught, the scientist will usually “test” the machine on some unseen data, where the scientist still knows what the correct answer is, but the machine doesn’t. The machine’s answers are compared to the known answers, and the machine’s accuracy can be measured. If the accuracy is high enough, the scientist may consider actually employing the algorithm in the real world.

https://pythonprogramming.net
https://twitter.com/sentdex
https://www.facebook.com/pythonprogramming.net/
https://plus.google.com/+sentdex

Artificial Intelligence 31 Resolution Explanation with Example in Ai
resolution is proof by contradiction
or you can say resolution is technique which uses negotiation to prove result
resolution basically is done in four steps
first resolution step is conversion of given statements into predicate logic
second resolution step is convert predicate logic into cnf or conjunctive normal form
third resolution step take negotiation of statement that is to be proved or contradict the statement that is to be proved in resolution
fourth step in resolution is resolve clause to get contradictory statement
in this video i have taken example of
cats like fish; cats eats everything they like;mani is cat;
to prove “mani eats fish”

How to process human language in a Recurrent Neural Network (LSTM / GRU) in TensorFlow and Keras. Demonstrated on Sentiment Analysis of the IMDB dataset.

https://github.com/Hvass-Labs/TensorFlow-Tutorials

** Machine Learning Training with Python: https://www.edureka.co/data-science-python-certification-course **
This Edureka video will provide you with a list of Machine Learning tools and Frameworks that one must know about.

Check out our playlist for more videos: http://bit.ly/2taym8X

Subscribe to our channel to get video updates. Hit the subscribe button above.

PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai

Post Graduate Certification in Data Science with IIT Guwahati – https://www.edureka.co/post-graduate/data-science-program
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)

#Edureka #MachineLearningEdureka #MachineLearningTools #MachineLearningUsingPython #MachineLearningTraining

How it Works?
1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

– – – – – – – – – – – – – – – – –
About the Course

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.

After completing this Machine Learning Certification Training using Python, you should be able to:
Gain insight into the ‘Roles’ played by a Machine Learning Engineer
Automate data analysis using python
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and it’s related concepts
Gain expertise to handle business in future, living the present

– – – – – – – – – – – – – – – – – – –

Why learn Machine Learning with Python?

Data Science is a set of techniques that enable the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free)

Instagram: https://www.instagram.com/edureka_lea…
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

🔥Intellipaat Artificial Intelligence Masters Course:- https://intellipaat.com/artificial-intelligence-masters-training-course/
In this Artificial Intelligence tutorial for beginners video you will learn all the major basic concepts in Artificial Intelligence like what is ai, difference between ai, ml and dl, topology of a neural network, how to train network with backpropagation with an in depth demo on tensorflow and keras.
#aiartificialintelligence #artificialintelligencecourse #whatisartificialintelligence #artificialintelligenceforbeginners #aitutorialforbeginners

📌 Do subscribe to Intellipaat channel & get regular updates on technological videos: http://bit.ly/Intellipaat

📝This artificial intelligence training video helps you to learn following topics:
00:57 – what makes human intelligent?
01:15 – what is artificial intelligence
01:30 – difference between ai, ml and dl
01:45 – why to study artificial intelligence
05:17 – artificial intelligence
07:20 – what is intelligence
08:27 – what makes human intelligent
09:37 – ai vs ml vs dl
11:50 – machine learning applications
17:15 – machine learning types
23:55 – machine learning algorithms
26:11 – what is deep learning
28:33 – deep learning applications
29:40 – how deep learning works
31:00 – what is neural network
31:51 – artificial neural networks
34:30 – artificial neurons
44:50 – deep learning frameworks

🔗 Watch Artificial Intelligence video tutorials here: https://goo.gl/gyf2g3

📕 Read complete Artificial Intelligence tutorial here: https://bit.ly/2nuITZg

📰Interested to learn Artificial Intelligence still more? Please check similar Blogs here:- https://goo.gl/rFFw9L

Are you looking for something more? Enroll in our Artificial Intelligence Course and become a certified A.I. professional (https://goo.gl/RdA17B). It is a 32 hrs instructor led AI for everyone training provided by Intellipaat which is completely aligned with industry standards and certification bodies.

If you’ve enjoyed this what is ai, ai vs ml video, Like us and Subscribe to our channel for more similar videos and free tutorials.
Got any questions? Ask us in the comment section below.
—————————-
Intellipaat Edge
1. 24*7 Life time Access & Support
2. Flexible Class Schedule
3. Job Assistance
4. Mentors with +14 yrs
5. Industry Oriented Course ware
6. Life time free Course Upgrade
——————————
Why should you watch this Artificial Intelligence tutorial?

You can learn Artificial Intelligence much faster than any other technology and this Artificial Intelligence tutorial helps you do just that. Artificial Intelligence is one of the best technological advances that is finding increased applications for machine learning and in a lot of industry domains. We are offering the top Artificial Intelligence tutorial that is AI for everyone to gain knowledge in Artificial Intelligence. Our Artificial Intelligence course has been created with extensive inputs from the industry experts so that you can learn Artificial Intelligence and apply it for real world scenarios.

Who should watch this Artificial Intelligence tutorial video?

If you want to learn Artificial Intelligence to become an A.I. expert then this Intellipaat Artificial Intelligence tutorial and AI deep learning course with tensorflow is for you. The Intellipaat Artificial Intelligence video is your first step to learn A.I. Since this A.I. tutorial and examples video can be taken by anybody, so if you are a beginner in technology then you can also watch other Artificial Intelligence tutorial to take your skills to the next level.

Why Artificial Intelligence is important?

Artificial Intelligence is taking over each and every industry domain. Machine Learning and especially Deep Learning are the most important aspects of Artificial Intelligence that are being deployed everywhere from search engines to online movie recommendations. Taking the Intellipaat deep learning training & Artificial Intelligence Course can help professionals to build a solid career in a rising technology domain and get the best jobs in top organizations.

Why should you opt for a Artificial Intelligence career?

If you want to fast-track your career then you should strongly consider Artificial Intelligence. The reason for this is that it is one of the fastest growing technology. There is a huge demand for professionals in Artificial Intelligence. The salaries for A.I. Professionals is fantastic.There is a huge growth opportunity in this domain as well. Hence this Intellipaat Artificial Intelligence tutorial is your stepping stone to a successful career!
——————————
For more Information:
Please write us to sales@intellipaat.com, or call us at: +91- 7847955955
Website: https://goo.gl/RdA17B

Facebook: https://www.facebook.com/intellipaatonline

LinkedIn: https://www.linkedin.com/in/intellipaat/

Twitter: https://twitter.com/Intellipaat

Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora.

Python for Data Science Certification Training Course: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=Data-Science-NLP-6WpnxmmkYys&utm_medium=Tutorials&utm_source=youtube

Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning, and follow the path towards your dream career- https://www.simplilearn.com/machine-learning-career-guide-pdf?utm_campaign=Data-Science-NLP-6WpnxmmkYys&utm_medium=Tutorials&utm_source=youtube

The Data Science with Python course is designed to impart an in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning, and natural language processing using Python. The course is packed with real-life projects, assignment, demos, and case studies to give a hands-on and practical experience to the participants.

Mastering Python and using its packages: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization.

Mastering advanced analytics techniques: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it’s modeling, and implementation using SAS.

As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis.

Who should take this course?
There is a booming demand for skilled data scientists across all industries that make this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
1. Analytics professionals who want to work with Python
2. Software professionals looking for a career switch in the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in Analytics and Data Science
5. Experienced professionals who would like to harness data science in their fields
6. Anyone with a genuine interest in the field of Data Science

For more updates on courses and tips follow us on:
– Facebook : https://www.facebook.com/Simplilearn
– Twitter: https://twitter.com/simplilearn

Get the android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0

Link To App: https://x.thunkable.com/copy/1f65f20d964f3f9477bf5a6836e17a0e
Learn how to build a camera app and an image recognition app!

This video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and more. Python, NLTK, & Jupyter Notebook are used to demonstrate the concepts.

This tutorial was developed by Edureka.

🔗NLP Certification Training: https://goo.gl/kn2H8T

🔗Subscribe to the Edureka YouTube channel: https://www.youtube.com/user/edurekaIN

🔗Edureka Online Training: https://www.edureka.co/

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://medium.freecodecamp.org

And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp

If you want to add biometric security features to your Arduino projects, an easy way to do so, is to add a fingerprint sensor module to it. In this video we demonstrate how easy to use a fingerprint sensor with an Arduino Nano and a small display.

I always wanted to try a fingerprint sensor module in order to learn more about its technology and use it in some of my projects in order to add biometric security to them. While searching for a nice and low cost sensor, I discovered this sensor module on Gearbest.com. The sensor costs around 30$ and you can find a link for it in the description of the video. Gearbest.com was kind enough to send a sample unit in order to test it and share my opinion about it with you.

——————–
WHERE TO BUY
——————–

Fingerprint Sensor: http://educ8s.tv/part/FingerprintSensor

Arduino Nano: http://educ8s.tv/part/ArduinoNano

1.44 Color TFT: http://educ8s.tv/part/LCD144

Small Breadboard: http://educ8s.tv/part/SmallBreadboard

Jumper Wires: http://educ8s.tv/part/JumperWires

Power bank Xiaomi: http://educ8s.tv/part/Powerbank

Full disclosure: All of the links above are affiliate links. I get a small percentage of each sale they generate. Thank you for your support!

The fingerprint sensor module is small, and nicely built and it uses some advanced DSP (Digital Signal Processing) chips inside. The sensor works like this. It is an optical sensor, which means it analyzes the photo of a finger. It then renders the image, makes some calculations, finds the features of that finger and then searches in its memory for a fingerprint with the same characteristics. It can achieve all that in less than a second! This module can store up to 1000 fingerprints in its memory and its false acceptance rate is less than 0.001% which makes it pretty secure! Great! We get all that in a very easy to use module and with very low cost! It is a really impressive technology!

In order to demonstrate a simple use of the sensor a built this simple project. I have hooked up the sensor to an Arduino Nano, and I also use the small but very fast 1.44 inch color TFT display. The project asks for a valid fingerprint in order to unlock. When I place my finger on the sensor, it recognizes my finger, turns the fingerprint icon green and it welcomes me. If my girlfriend places her finger on the sensor, it also recognizes her, and displays a welcome message with her name. If I place another finger on the sensor, the project does not unlock the screen. It works fine and you are going to see, you can build this project in less than 10 minutes! Let’s see how to achieve that!

——————–
LIBRARIES
——————–

https://github.com/adafruit/Adafruit-Fingerprint-Sensor-Library

https://github.com/adafruit/Adafruit-GFX-Library

https://github.com/sumotoy/TFT_ILI9163C

——————–
CODE OF THE PROJECT
——————–

Fingerprint Sensor with Arduino

——————–
Quiz of Knowledge Android Game
——————–

You can download my latest Android Game which is called Quiz of Knowledge here:

📥 http://bit.ly/QuizOfKnowledge

——————–
MORE PROJECTS
——————–
Arduino Datalogger: https://www.youtube.com/watch?v=oei3Y6tOhVI
Arduino Weather Station Project: https://www.youtube.com/watch?v=9jN-3DtS1RI
Arduino Nokia 5110 LCD Display: https://www.youtube.com/watch?v=aDwrMeu4k9Y
Arduino OLED display tutorial: https://www.youtube.com/watch?v=A9EwJ7M7OsI
DIY Arduino: https://www.youtube.com/watch?v=npc3uzEVvc0

——————–
ABOUT EDUC8S.TV
——————–
Educ8s.tv is a Youtube channel and website which is dedicated in developing high quality videos about DIY hardware and software projects. In this channel we develop projects with Arduino, Raspberry Pi, we build robots and simple electronic circuits. Check out our website as well for more information: http://www.educ8s.tv

——————–
SUBSCRIBE ON YOUTUBE
——————–

Never miss a video: https://www.youtube.com/subscription_center?add_user=educ8s

This video on Deep Learning with Python will help you understand what is deep learning, applications of deep learning, what is a neural network, biological versus artificial neural networks, introduction to TensorFlow, activation function, cost function, how neural networks work, and what gradient descent is. Deep learning is a technology that is used to achieve machine learning through neural networks. We will also look into how neural networks can help achieve the capability of a machine to mimic human behavior. We’ll also implement a neural network manually. Finally, we’ll code a neural network in Python using TensorFlow.

Below topics are explained in this Deep Learning with Python tutorial:
1. What is Deep Learning (01:56)
2. Biological versus Artificial Intelligence (02:45)
3. What is a Neural Network (04:09)
4. Activation function (08:49)
5. Cost function (14:08)
6. How do Neural Networks work (16:05)
7. How do Neural Networks learn (18:58)
8. Implementing the Neural Network (20:26)
9. Gradient descent (23:21)
10. Deep Learning platforms (24:48)
11. Introduction to TensoFlow (26:00)
12. Implementation in TensorFlow (28:56)

To learn more about Deep Learning, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

To access the slides, click here: https://www.slideshare.net/Simplilearn/deep-learning-with-python-deep-learning-and-neural-networks-deep-learning-tutorial-simplilearn/Simplilearn/deep-learning-with-python-deep-learning-and-neural-networks-deep-learning-tutorial-simplilearn

Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

#DeepLearningWithPython #DeepLearningTutorial #DeepLearning #Datasciencecourse #DataScience #SimplilearnMachineLearning #DeepLearningCourse

Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you’ll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as deep learning scientist.

Why Deep Learning?

It is one of the most popular software platforms used for deep learning and contains powerful tools to help you build and implement artificial neural networks.
Advancements in deep learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in deep learning models, learn to operate TensorFlow to manage neural networks and interpret the results.

With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations, and the execution pipeline
2. Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
4. Build deep learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial neural networks
6. Troubleshoot and improve deep learning models
7. Build your own deep learning project
8. Differentiate between machine learning, deep learning and artificial intelligence

There is booming demand for skilled deep learning engineers across a wide range of industries, making this deep learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this deep learning online course particularly for the following professionals:

1. Software engineers
2. Data scientists
3. Data analysts
4. Statisticians with an interest in deep learning

Learn more at: https://www.simplilearn.com/deep-learning-course-with-tensorflow-training?utm_campaign=Deep-Learning-with-Python-fcD6YeEYKNg&utm_medium=Tutorials&utm_source=youtube

For more information about Simplilearn’s courses, visit:
– Facebook: https://www.facebook.com/Simplilearn
– Twitter: https://twitter.com/simplilearn
– LinkedIn: https://www.linkedin.com/company/simplilearn/
– Website: https://www.simplilearn.com

Get the Android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0

Joscha Bach and Ronnie Vuine give a tutorial on the MicroPsi cognitive architecture at the Seventh Conference on Artificial General Intelligence (AGI-14) in Quebec City (http://www.agi-conference.org/2014). Joscha starts with explaining the high level ideas and around 1:38:40 Ronnie starts giving some demonstrations of the software.

The MicroPsi agent architecture describes the interaction of emotion, motivation and cognition of situated agents, mainly based on the Psi theory of Dietrich Dörner. The Psi theory addresses emotion, perception, representation and bounded rationality, but being formulated within psychology, has had relatively little impact on the discussion of agents within computer science. MicroPsi is a formulation of the original theory in a more abstract and formal way, at the same time enhancing it with additional concepts for memory, building of ontological categories and attention.

More information can be found at http://micropsi.com/.

This Deep Learning tutorial is designed for beginners who want to learn Deep Learning from scratch. We will look at where Deep Learning is applied and what exactly this term means. We’ll see how Deep Learning, Machine Learning, and AI are different and why Deep Learning even came into the picture. We will then proceed to look at Neural Networks, which are the core of Deep Learning. Before we move into the working of Neural Networks, we’ll cover activation and cost functions. The video will also introduce you to the most popular Deep Learning platforms. We wrap it up with a demo in TensorFlow to predict if a person receives a salary above or below 50k. Now, let us get started and understand Deep Learning in detail.

Below topics are explained in this Deep Learning tutorial:
1. Applications of Deep Learning
2. What is Deep Learning
3. Why is Deep Learning important
4. What are Neural Networks
5. Activation function
6. Cost function
7. How do Neural Networks work
8. Deep Learning platforms
9. Introduction to TensorFlow
10. Use case implementation using TensorFlow

To learn more about Deep Learning, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

#DeepLearningTutorial #DeepLearning #DeepLearningAndNeuralNetworks #WhatIsDeepLearning#DeepLearningCourse #Simplilearn

Simplilearn’s Deep Learning course will transform you into an expert in Deep Learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our Deep Learning course, you’ll master Deep Learning and TensorFlow concepts, learn to implement algorithms, build artificial Neural Networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as Deep Learning scientist.

Why Deep Learning?

It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial Neural Networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in Deep Learning models, learn to operate TensorFlow to manage Neural Networks and interpret the results. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.

You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement Deep Learning algorithms, understand Neural Networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional Neural Networks, recurrent Neural Networks, training deep networks and high-level interfaces
4. Build Deep Learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial Neural Networks
6. Troubleshoot and improve Deep Learning models
7. Build your own Deep Learning project
8. Differentiate between machine learning, Deep Learning and artificial intelligence

There is booming demand for skilled Deep Learning engineers across a wide range of industries, making this Deep Learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this Deep Learning online course particularly for the following professionals:

1. Software engineers
2. Data scientists
3. Data analysts
4. Statisticians with an interest in Deep Learning

Learn more at: https://www.simplilearn.com/deep-learning-course-with-tensorflow-training?utm_campaign=Deep-Learning-Tutorial-Cq_P8kJgjvI&utm_medium=Tutorials&utm_source=youtube

For more information about Simplilearn’s courses, visit:
– Facebook: https://www.facebook.com/Simplilearn
– Twitter: https://twitter.com/simplilearn
– LinkedIn: https://www.linkedin.com/company/simplilearn/
– Website: https://www.simplilearn.com

Get the Android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0

Hello All,
In this video we will be discussing about the differences Between Infrastructure as a Service and Platform as a Service cloud platforms

Support me in Patreon: https://www.patreon.com/join/2340909?

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=ac229c9a45954acc19c1b2fa2ca96e23&creativeASIN=1789346371

Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
amazon url:
https://www.amazon.in/Hands-Machine-Learning-Scikit-Learn-Tensor/dp/9352135210/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=a706a13cecffd115aef76f33a760e197&creativeASIN=9352135210

Connect with me here:
Twitter: https://twitter.com/Krishnaik06
Facebook: https://www.facebook.com/krishnaik06
instagram: https://www.instagram.com/krishnaik06

Subscribe my unboxing Channel

https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw

Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1

🙏🙏🙏🙏🙏🙏🙏🙏
YOU JUST NEED TO DO
3 THINGS to support my channel
LIKE
SHARE
&
SUBSCRIBE
TO MY YOUTUBE CHANNEL

🔥 Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training
This Edureka video on “Artificial Intelligence” will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples.

Following topics are covered in this video:
02:27 History Of AI
06:45 Demand For AI
08:46 What Is Artificial Intelligence?
09:50 AI Applications
16:49 Types Of AI
20:24 Programming Languages For AI
27:12 Introduction To Machine Learning
28:08 Need For Machine Learning
31:48 What Is Machine Learning?
34:13 Machine Learning Definitions
37:26 Machine Learning Process
49:13 Types Of Machine Learning
49:21 Supervised Learning
52:00 Unsupervised Learning
53:44 Reinforcement Learning
55:29 Supervised vs Unsupervised vs Reinforcement Learning
58:23 Types Of Problems Solved Using Machine Learning
1:04:49 Supervised Learning Algorithms
1:05:17 Linear Regression
1:11:20 Linear Regression Demo
1:26:36 Logistic Regression
1:35:36 Decision Tree
1:55:18 Random Forest
2:07:31 Naive Bayes
2:14:37 K Nearest Neighbour (KNN)
2:20:31 Support Vector Machine (SVM)
2:26:40 Demo (Classification Algorithms)
2:42:36 Unsupervised Learning Algorithms
2:42:45 K-means Clustering
2:50:49 Demo (Unsupervised Learning)
2:56:40 Reinforcement Learning
3:24:36 Demo (Reinforcement Learning)
3:31:41 AI vs Machine Learning vs Deep Learning
3:33:08 Limitations Of Machine Learning
3:36:32 Introduction To Deep Learning
3:38:36 How Deep Learning Works?
3:40:48 What Is Deep Learning?
3:41:50 Deep Learning Use Case
3:43:14 Single Layer Perceptron
3:50:56 Multi Layer Perceptron (ANN)
3:52:55 Backpropagation
3:54:39 Training A Neural Network
4:01:02 Limitations Of Feed Forward Network
4:03:18 Recurrent Neural Networks
4:05:36 Convolutional Neural Networks
4:09:00 Demo (Deep Learning)
4:29:02 Natural Language Processing
4:30:53 What Is Text Mining?
4:32:43 What Is NLP?
4:33:26 Applications Of NLP
4:35:53 Terminologies In NLP
4:41:19 NLP Demo
4:47:21 Machine Learning Masters Program

————————–

Python Course: https://www.youtube.com/watch?v=vaysJAMDaZw
Statistics and Probability Tutorial: https://www.youtube.com/watch?v=XcLO4f1i4Yo

Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV

Check out the entire Machine Learning Playlist: https://bit.ly/2NG9tK4

#edureka #aiEdureka #artificialIntelligence #artificialIntelligenceTutorial #artificialIntelligenceFullCourse #artificialIntelligenceEngineer

Instagram: https://www.instagram.com/edureka_learning
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Slideshare: https://www.slideshare.net/EdurekaIN/

————————————-

About the Masters Program

Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.

The Master’s Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markov’s Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods.

———————-

Prerequisites

There are no prerequisites for enrolment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

————————————–

Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information

Can AI be used to detect various diseases from a simple body scan? Yes! Normally, doctors train for years to do this and the error rate is still relatively high. From mammograms to cat scans, AI can diagnose a disease better than any human can if given the right training dataset. This will drastically reduce patient death, save medical practices a lot of money, and aid doctors in the patient care process. Everyone will win and its important to remember that AI won’t replace doctors, it will become the most powerful tool they’ve ever used. And once enough AI startups start impacting the field of healthcare, it will become as common a tool as the stethoscope has been.

Code for this video:
https://github.com/llSourcell/AI_in_Medicine_Clinical_Imaging_Classification

Please Subscribe! And like. And comment. That’s what keeps me going.

Want more education? Connect with me here:
Twitter: https://twitter.com/sirajraval
Facebook: https://www.facebook.com/sirajology
instagram: https://www.instagram.com/sirajraval

Curriculum:
https://github.com/llSourcell/AI_For_Business_Curriculum

More learning resources:
https://www.youtube.com/watch?v=3LkbUxqGTfo
https://www.youtube.com/watch?v=S4GvBCMfRew
https://www.youtube.com/watch?v=LxHHsujnF9c
https://www.youtube.com/watch?v=ZPXCF5e1_HI
https://www.youtube.com/watch?v=QfNvhPx5Px8&t=202s

Join us in the Wizards Slack channel:
http://wizards.herokuapp.com/

Sign up for the next course at The School of AI:
https://www.theschool.ai

https://github.com/gregwchase/dsi-capstone

And please support me on Patreon:
https://www.patreon.com/user?u=3191693
Signup for my newsletter for exciting updates in the field of AI:
https://goo.gl/FZzJ5w
Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

HOW TO MAKE IMAGE RECOGNITION BOT VERY EASY AND FUN TUTORIAL WITH SIKULI

by Dolce Panna
Download Java from here
http://www.java.com/en/download

Download Sikuli from here
https://launchpad.net/sikuli/sikulix/x1.0-rc3/+download/Sikuli-X-1.0rc3%20%28r905%29-win32.exe

** RPA Training using UiPath – https://www.edureka.co/robotic-process-automation-training **
In this Edureka “UiPath Tutorial For Beginners” you will get an introduction to the leading RPA tool – Uipath. Towards the end, we will also be doing hands-on using UiPath. Below are the topics covered in this UiPath Tutorial:

00:48 What is RPA?
2:03 RPA Tools
3:40 Installing UiPath

Get Started with UiPath
5:49 Activities
6:35 Sequences

Types of Projects in UiPath Studio
7:23 Blank Project
7:54 Simple Process
8:49 Agent Process Improvement
10:19 Transactional Business Process
12:03 UiPath Components
13:49 Ribbon
13:52 Recording
17:42 Scraping
18:45 User Events
19:23 Variables
22:35 Activity Pane
24:21 UI Automation
25:49 User Events
26:17 UiPath Orchestrator
26:49 System
27:29 Programming
27:34 Workflow
29:17 Properties Pane
30:34 Control Bar
31:59 Hands-On

Subscribe to our channel to get video updates. Hit the subscribe button above.

How it Works?

1. This is a 4 Week Instructor led Online Course, 25 hours of assignment and 20 hours of project work
2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to work on a project, based on which we will provide you a Grade and a Verifiable Certificate!

– – – – – – – – – – – – – –

About the Course

Edureka’s RPA training makes you an expert in Robotic Process Automation.. Robotic Process Automation is Automation of repetitive and rule based tasks. In Edureka’s RPA online training, you will learn about the RPA concepts and will gain in-depth knowledge on UiPath tool using which you can automate the data extraction from the internet, login process, image recognition process and many more.

After completing the RPA Training, you will be able to:

1. Know about Robotic Process Automations and how it works
2. Know about the patterns and key considerations while designing a RPA solution
3. Know about the leading RPA tool i.e. UiPath
4. Gain practical knowledge on designing RPA solutions using both the tools
5. Perform Image and Text automation
6. Create RPA bots and perform data manipulation
7. Debug and handle the exceptions through the tool

– – – – – – – – – – – – – –

Why learn Robotic Process Automation?

Robotic Process Automation (RPA) is an automation technology for making smart software by applying intelligence to do high volume and repeatable tasks that are time-consuming. RPA is automating the tasks of wide variety of industries, hence reducing the time and increasing the output. Some of facts about RPA includes:

1. A 2016 report by McKinsey and Co. predicts that the robotic process automation market could be worth $6.7 trillion by 2025

2. A major global wine business, after implementing RPA, increased the order accuracy from 98% to 99.7% while costs reduced to Rs. 5.2 Crore

3. A global dairy company used RPA to automate the processing and validation of delivery claims, reduced goodwill write-offs by Rs. 464 Million

For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Telegram: https://t.me/edurekaupdates

Organizers: Jason (Jinquan) Dai Location: Room 151 A-C & G Time: 0900-1200 (Half Day — Morning) Description: Recent breakthroughs in artificial intelligence applications have brought deep learning to the forefront of new generations of data analytics. In this tutorial, we will pre-sent the practice and design tradeoffs for building large-scale deep learning applications (such as computer vision and NLP) for production data and workflow on Big Data platforms. In particular, we will provide an overview of emerging deep learn-ing frameworks for Big Data (e.g., BigDL, TensorFlow-on-Spark, Deep Learning Pipelines for Spark, etc.), present the underlying distributed systems and algorithms, and discuss innovative data analytics + AI application pipelines (with a focus on computer vision models and use cases) for Big Data platforms and workflows. Schedule: 0900 Motivation 0910 Overview 0930 Analytics Zoo for Spark and BigDL 1000 Morning Break 1030 Distributed Training and Inference 1100 Advanced Applications 1130 Real-World Applications 1150 Q&A

We’re stoked to combine the power of Hololens and Vuforia to start building AR prototypes, especially given the Hololens competition Unity just announced. To get everyone up to speed, here’s a video on how to set up image recognition. Comment below if you have ideas on what you would like us to build next! As a last note, you don’t need a Hololens to follow along. Vuforia has a great Unity emulator.

Hololens Academy: https://developer.microsoft.com/en-us/windows/mixed-reality/academy
Install the Tools: https://developer.microsoft.com/en-us/windows/mixed-reality/install_the_tools
Vuforia for Hololens: https://library.vuforia.com/articles/Training/Developing-Vuforia-Apps-for-HoloLens

Welcome to the weekly FusedVR Tutorials! These videos/streams are a chance not only for anyone to learn more about AR/VR development, but also a chance for anyone to ask questions about LITERALLY anything! Whether it be about your own AR/VR development, your future projects, or just AR/VR in general, we would love to talk with you about it!

Suggestions for future streams. Post Here: http://fusedvr.com

If you missed last week’s stream, here is a link to that video where we go over how to build fireballs like in Street Fighter or Dragon Ball Z:

Interested in keeping up to date with the live streams? Follow us on social media or subscribe to the channel!

https://www.facebook.com/FusedVR/
https://twitter.com/FusedVR
http://bit.ly/1SZXwtn