** 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

——————————————————————————————————–

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➡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.
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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!
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🔥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

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📝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

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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.
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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
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🔥 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

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————————————-

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

So we’ve talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving cars, to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence. We may be a long way from self-aware computers that think just like us, but with advancements in deep learning and artificial neural networks our computers are becoming more powerful than ever.

Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios

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Today Hank explores artificial intelligence, including weak AI and strong AI, and the various ways that thinkers have tried to define strong AI including the Turing Test, and John Searle’s response to the Turing Test, the Chinese Room. Hank also tries to figure out one of the more personally daunting questions yet: is his brother John a robot?

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Watch this Python tutorial to learn Python programming for machine learning and web development.
🔥Get My Complete Python Programming Course with a 90% Discount (LIMITED to the first 200 students):
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#Python, #MachineLearning, #WebDevelopment

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TABLE OF CONTENT

00:00:00 Introduction
00:01:49 Installing Python 3
00:06:10 Your First Python Program
00:08:11 How Python Code Gets Executed
00:11:24 How Long It Takes To Learn Python
00:13:03 Variables
00:18:21 Receiving Input
00:22:16 Python Cheat Sheet
00:22:46 Type Conversion
00:29:31 Strings
00:37:36 Formatted Strings
00:40:50 String Methods
00:48:33 Arithmetic Operations
00:51:33 Operator Precedence
00:55:04 Math Functions
00:58:17 If Statements
01:06:32 Logical Operators
01:11:25 Comparison Operators
01:16:17 Weight Converter Program
01:20:43 While Loops
01:24:07 Building a Guessing Game
01:30:51 Building the Car Game
01:41:48 For Loops
01:47:46 Nested Loops
01:55:50 Lists
02:01:45 2D Lists
02:05:11 My Complete Python Course
02:06:00 List Methods
02:13:25 Tuples
02:15:34 Unpacking
02:18:21 Dictionaries
02:26:21 Emoji Converter
02:30:31 Functions
02:35:21 Parameters
02:39:24 Keyword Arguments
02:44:45 Return Statement
02:48:55 Creating a Reusable Function
02:53:42 Exceptions
02:59:14 Comments
03:01:46 Classes
03:07:46 Constructors
03:14:41 Inheritance
03:19:33 Modules
03:30:12 Packages
03:36:22 Generating Random Values
03:44:37 Working with Directories
03:50:47 Pypi and Pip
03:55:34 Project 1: Automation with Python
04:10:22 Project 2: Machine Learning with Python
04:58:37 Project 3: Building a Website with Django

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This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future.
Who is this class for: This class is for people who would like to learn more about machine learning techniques, but don’t currently have the fundamental mathematics in place to go into much detail. This course will include some exercises that require you to work with code. If you’ve not had much experience with code before DON’T PANIC, we will give you lots of guidance as you go.
Topic Covered:
Fuctions
Definition of a derivative
Differentiation examples & special cases
differentiate some functions
Time saving rules
Product rule
Chain rule
Variables, constants & context
Differentiate with respect to anything
Jacobians – vectors of derivatives
Jacobian applied
The Sandpit
The Sandpit -2
The Hessian
Multivariate chain rule
Neural Networks
Simple neural networks
Power series
Visualising Taylor Series
Power series derivation
Power series details
Multivariable Taylor Series
Linearisation
Multivariate Taylor
Gradient Descent
Gradient descent in a sandpit
Lagrange multipliers
Constrained optimisation
Simple linear regression
Non-linear regression
******************************************************************
This course is created by Imperial College London
If you like this video and course explanation feel free to take the
complete course and get certificate from: https://www.coursera.org/specializations/mathematics-machine-learning

This video is provided here for research and educational purposes in the field of Mathematics. No copyright infringement intended. If you are content owner would like to remove this video from YouTube, Please contact me through email: ict_hanif@yahoo.com
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