AI - Natural Language Processing (NLP) with Python
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Frontier Education
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Overview
AI - Natural Language Processing (NLP) with Python
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Understand every detail and build real stuff in NLP
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Learn how some plugins use semantic search to generate source code
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Building your vocabulary for any NLP model
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Reducing Dimensions of your Vocabulary for Machine Learning Models
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Feature Engineering and convert text to numerical values for machine learning models
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Keyword search VS Semantic search
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Similarity between documents
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Dealing with WordNet
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Search engines under the hood
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Tokenizing text data
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Converting words to their base forms using stemming
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Converting words to their base forms using lemmatization
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Dividing text data into chunks
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Dealing with corpuses
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Extracting document term matrix using the Bag of Words model
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Building a category predictor
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Constructing a gender identifier
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Building a sentiment analyzer
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Topic modeling using Latent Dirichlet Allocation
Certificates
Reed courses certificate of completion
Digital certificate - Included
Will be downloadable when all lectures have been completed
Curriculum
Course media
Description
THIS COURSE IS FOR BEGINERS OR INTERMEDIATES, IT IS NOT FOR EXPERTS
This course is focusing on the NLP:
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Learn key NLP concepts and intuition training to get you quickly up to speed with all things NLP.
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I will give you the information in an optimal way, I will explain in the first video for example what is the concept, and why is it important, what is the problem that led to thinking about this concept and how can I use it (Understand the concept). In the next video, you will go to practice in a real-world project or in a simple problem using python (Practice).
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The first thing you will see in the video is the input and the output of the practical section so you can understand everything and you can get a clear picture!
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You will have all the resources at the end of this course, the full code, and some other useful links and articles.
In this course, we are going to learn about natural language processing. We will discuss various concepts such as tokenization, stemming, and lemmatization to process text. We will then discuss how to build a Bag of Words model and use it to classify text. We will see how to use machine learning to analyse the sentiment of a given sentence. We will then discuss topic modeling and implement a system to identify topics in a given document. We will start with simple problems in NLP such as Tokenization Text, Stemming, Lemmatization, Chunks, Bag of Words model. and we will build some real stuff such as :
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Learning How to Represent the Meaning of Natural Language Text
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Building a category predictor to predict the category of a given text document.
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Constructing a gender identifier based on the name.
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Building a sentiment analyzer used to determine whether a movie review is positive or negative.
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Topic modeling using Latent Dirichlet Allocation
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Feature Engineering
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Dealing with corpora and WordNet
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Dealing With your Vocabulary for any NLP and ML model
Curriculum
Lecture 1:Note!
Lecture 2:Introduction to NLP
Lecture 3:By The End Of This Section
Lecture 4:Installation
Lecture 5:Tips
Lecture 6:U - Tokenization
Lecture 7:P - Tokenization
Lecture 8:U - Stemming
Lecture 9:P - Stemming
Lecture 10:U - Lemmatization
Lecture 11:P - Lemmatization
Lecture 12:U - Chunks
Lecture 13:P - Chunks
Lecture 14:U - Bag Of Words
Lecture 15:P - Bag Of Words
Lecture 16:U - Category Predictor
Lecture 17:P - Category Predictor
Lecture 18:U - Gender Identifier
Lecture 19:P - Gender Identifier
Lecture 20:U - Sentiment Analyzer
Lecture 21:P - Sentiment Analyzer
Lecture 22:U - Topic Modeling
Lecture 23:P - Topic Modeling
Lecture 24:Summary
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Who is this course for?
- Anyone who wants to understand NLP concepts and build some projects
- Beginner python developers curios about NLP, this course is not for experienced data scientists
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This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.