Learn from experts how to succeed with AI and automation. Watch the full recording of UiPath Live! https://bit.ly/3aIXwl7

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– monitoring and reading invoices in a PDF format,
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– opening and filling in invoice details in SAP,
– sending email notifications, as well as other background activities.

Discover more about what #RPA can do for your #Finance & Accounting department -http://bit.ly/2NoHnH4.

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Now that we understand some of the basics of of natural language processing with the Python NLTK module, we’re ready to try out text classification. This is where we attempt to identify a body of text with some sort of label.

To start, we’re going to use some sort of binary label. Examples of this could be identifying text as spam or not, or, like what we’ll be doing, positive sentiment or negative sentiment.

Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1

sample code: http://pythonprogramming.net

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Natural Language Processing (NLP) is a field of computer science that aims to understand or generate human languages, either in text or speech form. Computers are programmed to identify written and spoken words. But to really communicate with people, they need to understand context. Learn more: https://accntu.re/2MX0rwT


Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If youโ€™re not an expert on AI or ML, donโ€™t worry — weโ€™re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney (@lmoroney).

In this first lesson weโ€™ll talk about how to represent words in a way that a computer can process them, with a view to later training a neural network to understand their meaning.

Hands-on Colab โ†’ https://goo.gle/2uO6Gee

NLP Zero to Hero playlist โ†’ https://goo.gle/nlp-z2h
Subscribe to the TensorFlow channel โ†’ https://goo.gle/TensorFlow

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This video covers Stanford CoreNLP Example.

GitHub link for example: https://github.com/TechPrimers/core-nlp-example

Stanford Core NLP: https://stanfordnlp.github.io/CoreNLP/
Stanford API example: https://stanfordnlp.github.io/CoreNLP/api.html

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GitHub: https://github.com/TechPrimers or https://techprimers.github.io/

Video Editing: iMovie

Intro Music: A Way for me (www.hooksounds.com)

#CoreNLP #TechPrimers

Transfer Learning in Natural Language Processing (NLP): Open questions, current trends, limits, and future directions. Slides: https://tinyurl.com/FutureOfNLP
A walk through interesting papers and research directions in late 2019/early-2020 on:
– model size and computational efficiency,
– out-of-domain generalization and model evaluation,
– fine-tuning and sample efficiency,
– common sense and inductive biases.
by Thomas Wolf (Science lead at HuggingFace)

HuggingFace on Twitter: https://twitter.com/huggingface
Thomas Wolf on Twitter: https://twitter.com/Thom_Wolf

The circuit diagram and Project programming can be downloaded by clicking on the link below

Arduino Image Processing based Entrance lock Control System

Download Libraries:

Image Processing based Eyepupil Tracking:

Human machine tracking using image processing:

Watch other tutorials:

9: Image processing based entrance control system

8: GSM and GPS based car accident location monitoring

7: GSM based GAS leakage detection and sms alert

6: Wireless Tongue controlled wheelchair

5: Human Posture Monitoring System

4: RFID based bike anti theft system

3: RFID based students attendance system

2: Piezo Electric generator

1: iot car parking monitoring system

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Project Description:

This is a very detailed tutorial on how to make image processing based human recognition system for entrance controlling. In this project we will be using Arduino uno for controlling the electronic door lock, The Arduino will receive command from the vb.net application when a human will be detected. We will be using xml file for human face detection. This xml file will be used in vb.net application to track a human face. The application designed in vb.net visual basic make use of the emguCv.


download haarcascades:


Purchase links for Components with best prices. ” Amazon”

WebCam night vision supported: best deal on Amazon

electronic lock:

Arduino uno:

Mega 2560:

2n2222 npn transistor:

10k Resistor

female DC power jack socket:

12v Adaptor:

Super Starter kit for Beginners

Jumper Wires:

Bread Board:

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About the Electronic Clinic:
Electronic Clinic is the only channel on YouTube that covers all the engineering fields. Electronic Clinic helps the students and workers to learn electronics designing and programming. Electronic Clinic has tutorials on
Gsm based projects ” gsm security system, gsm messages sending and receiving, gsm based controlling, gsm based request data”

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electronics projects
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and much more.

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Crazy Cake Making Machines AWESOME FOOD PROCESSING | Amazing Cake Automated Processing Machines in Factory – Cream Cake, Cheese Cake & Chocolate Cake

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Track: Diviners – Savannah (feat Philly K) [NCS Release]
Music provided by NoCopyrightSounds.
Free Download / Stream: http://ncs.io/savannah
Watch: https://www.youtube.com/watch?v=u1I9ITfzqFs

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For more information go to https://curiositystream.com/crashcourse
So far in this series, we’ve mostly focused on how AI can interpret images, but one of the most common ways we interact with computers is through language – we type questions into search engines, use our smart assistants like Siri and Alexa to set alarms and check the weather, and communicate across language barriers with the help of Google Translate. Today, we’re going to talk about Natural Language Processing, or NLP, show you some strategies computers can use to better understand language like distributional semantics, and then we’ll introduce you to a type of neural network called a Recurrent Neural Network or RNN to build sentences.

Crash Course AI is produced in association with PBS Digital Studios

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#CrashCourse #ArtificialIntelligence #MachineLearning

Natural language processing (Wikipedia): โ€œNatural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages

Intelligent technology in egg factory;
smart machines, automatic machinery egg processing, egg collecting and egg separating machines.
Intelligent Technology Egg Processing Machines โ˜… Smart Machines Egg Collecting Separating in Factory

Natural Language Processing techniques allow addressing tasks like text classification and information extraction and content generation. They can give the perception of machines being able to understand humans and respond more naturally.

In this session, Barbara will introduce basic concepts of natural language processing. Using Python and its machine learning libraries the attendees will go through the process of building the bag of words representation and using it for text classification. It can be then used to recognise the sentiment, category or the authorship of the document.
The goal of this tutorial is to build the intuition on the simple natural language processing task. After this session, the audience will know basics of the text representation, learn how to develop the classification model and use it in real-world applications.

NDC Conferences

Learn most important Natural Language Processing Interview Questions and Answers, asked at every Artificial Intelligence interview. These Interview questions will be useful to all entry level candidates, beginners, interns and experienced candidates interviewing for the role of NLP Engineer, NLP Researcher, NLP Intern etc.
The examples and sample answers with each question will make it easier for candidates to understand these conceptual, general and situational interview questions.

Our Websites:

#NaturalLanguageProcessing #NLPInterview #NLPForBeginners

Natural Language Processing , Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English.
Natural Language Understanding (NLU)
Natural Language Generation (NLG)

Natural Language Processing, or NLP, is made up of Natural Language Understanding and Natural Language Generation. NLU helps the machine understand the intent of the sentence or phrase using profanity filtering, sentiment detection, topic classification, entity detection, and more.

In this episode, Tia breaks down the differences between NLP, NLU, and NLG, and explains how Deep Learning plays a role in getting you better search results, faster.

For more information on all things AI, subscribe to the Lucid Thoughts channel!

Presentation by Catherine Henry (2017 Clearwater DevCon).
When teaching a subject through text it can be beneficial to evaluate the readerโ€™s understanding; however, the creation of relevant questions and answers can be time-consuming and tedious. I will walk through how the implementation of NLP libraries and algorithms can assist in, and potentially remove altogether, the current necessity of an individual manually formulating these tests.

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

Natural language processing is a subfield of artificial intelligence (AI) concerned with the interactions between computers and human languages. It was formulated to build software that generates and comprehends natural languages so that a user can have natural conversations with the computer instead of through programming or artificial languages like Java or C. In this video, we will be learning all about Natural Language Processing (NLP), its various aspects and what the future holds for NLP.
Stay tuned to learn more about NLP with Great Learning!
#NaturalLanguageProcessing #ArtificialIntelligence #GreatLearning

Read more on NLP:

About Great Learning:

– Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more.

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Natural language processing allows computers to understand human language. It has plenty of applications. For example:
Text summarization, translation, keyword generation, sentiment analysis or chat bots.

So how it works? Letโ€™s take a closer look at it.

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๐Ÿ”ฅIntellipaat natural language processing in python course: https://intellipaat.com/nlp-training-course-using-python/
In this natural language processing tutorial video you will learn what is natural language, text mining in nlp, file handling in python, nltk package, tokenization, frequency distribution, stop words and the concepts of bi grams, tri grams and n grams in detail.
#NaturalLanguageProcessingNLPinPython #NaturalLanguageProcessingTutorial #NaturalLanguageProcessing #Intellipaat

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๐Ÿ”—Watch complete AI tutorials here: https://bit.ly/2YTKB7u

Are you looking for something more? Enroll in our natural language processing Course and become a certified professional (https://intellipaat.com/nlp-training-course-using-python/). It is a 20 hrs instructor led training provided by Intellipaat which is completely aligned with industry standards and certification bodies.

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Why should you watch this natural language processing tutorial?

NLP market is speculated to grow to US$26.4 billion by 2024 with CAGR of 21%. One of the principal disciplines of AI, Natural language processing is used to solve uses analysis tools to read data from large amounts of natural language data to arrive at meaningful conclusions. It involves using the ML algorithms to recognize, categorize, and extract natural language rules to transform unstructured language data into a form that computers can understand.

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 & deep learning tutorial is your stepping stone to a successful career!
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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

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Using AutoML NLP (Natural Language Processing) to classify and predict multilabel texts with a custom model. The demo consists of 3 parts:
– Uploading dataset
– Training
– Evaluating results and prediction

Download .csv here: https://cloud.google.com/natural-language/automl/docs/sample/happiness.csv

Thank you!

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

– Natural Language Processing (Part 1): Introduction to NLP & Data Science
– Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
– Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
– Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
– Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
– Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

– Natural Language Processing (Part 1): Introduction to NLP & Data Science
– Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
– Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
– Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
– Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
– Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial


UiPath Robot at work – Entering invoice data into SAP.
The robot opens the email, downloads and reads a PDF invoice. It then logs in SAP, enters all the required data and parks the invoice. It then confirms the successful execution and moves the email from the NPO Invoices to the Processed folder.

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

– Natural Language Processing (Part 1): Introduction to NLP & Data Science
– Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
– Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
– Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
– Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
– Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial

Not sure what natural language processing is and how it applies to you? In this video, we lay out the basics of natural language processing so you can better understand what it is, how it works, and how it’s being used in the real world today.

To learn more on how SparkCognition is taking artificial intelligence into the real world, check out our DeepNLP solution: http://bit.ly/2VsFv4I

Much of the Text Mining needed in real-life boils down to Text Classification: be it prioritising e-mails received by Customer Care, categorising Tweets aired towards an Organisation, measuring impact of Promotions in Social Media, and (Aspect based) Sentiment Analysis of Reviews. These techniques can not only help gauge the customerโ€™s feedback, but also can help in providing users a better experience.

Traditional solutions focused on heavy domain-specific Feature Engineering, and thats exactly where Deep Learning sounds promising!

We will depict our foray into Deep Learning with these classes of Applications in mind. Specifically, we will describe how we tamed Deep Convolutional Neural Network, most commonly applied to Computer Vision, to help classify (short) texts, attaining near-state-of-the-art results on several SemEval tasks consistently, and a few tasks of importance to Flipkart.

In this talk, we plan to cover the following:

Basics of Deep Learning as applied to NLP: Word Embeddings and its compositions a la Recursive Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks.

New Experimental results on an array of SemEval / Flipkartโ€™s internal tasks: e.g. Tweet Classification and Sentiment Analysis. (As an example we achieved 95% accuracy in binary sentiment classification task on our datasets – up from 85% by statistical models)

Share some of the learnings we have had while deploying these in Flipkart!

Here is a mindmap explaining the flow of content and key takeawys for the audience: https://atlas.mindmup.com/2015/06/4cbcef50fa6901327cdf06dfaff79cf0/deep_learning_for_natural_language_proce/index.html

We have decided to open source the code for this talk as a toolkit. https://github.com/flipkart-incubator/optimus Feel free to use it to train your own classifiers, and contribute!

( **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

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– – – – – – – – – – – – – –

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 textโ€“ 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 ?

Edurekaโ€™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 โ€˜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 everyoneโ€


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).

Lecture Series on Artificial Intelligence by Prof.Sudeshna Sarkar and Prof.Anupam Basu, Department of Computer Science and Engineering,I.I.T, Kharagpur . For more details on NPTEL visit http://nptel.iitm.ac.in.

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