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Course Curriculum

Course Curriculum

Unit 01: Getting an Idea of NLP and its Applications
Module 01: Introduction to NLP 00:03:00
Module 02: By the End of This Section 00:01:00
Module 03: Installation 00:04:00
Module 04: Tips 00:01:00
Module 05: U – Tokenization 00:01:00
Module 06: P – Tokenization 00:02:00
Module 07: U – Stemming 00:02:00
Module 08: P – Stemming 00:05:00
Module 09: U – Lemmatization 00:02:00
Module 10: P – Lemmatization 00:03:00
Module 11: U – Chunks 00:02:00
Module 12: P – Chunks 00:05:00
Module 13: U – Bag of Words 00:04:00
Module 14: P – Bag of Words 00:04:00
Module 15: U – Category Predictor 00:05:00
Module 16: P – Category Predictor 00:06:00
Module 17: U – Gender Identifier 00:01:00
Module 18: P – Gender Identifier 00:08:00
Module 19: U – Sentiment Analyzer 00:02:00
Module 20: P – Sentiment Analyzer 00:07:00
Module 21: U – Topic Modeling 00:03:00
Module 22: P – Topic Modeling 00:06:00
Module 23: Summary 00:01:00
Unit 02: Feature Engineering
Module 01: Introduction 00:02:00
Module 02: One Hot Encoding 00:02:00
Module 03: Count Vectorizer 00:04:00
Module 04: N-grams 00:04:00
Module 05: Hash Vectorizing 00:02:00
Module 06: Word Embedding 00:11:00
Module 07: FastText 00:04:00
Unit 03: Dealing with corpus and WordNet
Module 01: Introduction 00:01:00
Module 02: In-built corpora 00:06:00
Module 03: External Corpora 00:08:00
Module 04: Corpuses & Frequency Distribution 00:07:00
Module 05: Frequency Distribution 00:06:00
Module 06: WordNet 00:06:00
Module 07: Wordnet with Hyponyms and Hypernyms 00:07:00
Module 08: The Average according to WordNet 00:07:00
Unit 04: Create your Vocabulary for any NLP Model
Module 01: Introduction and Challenges 00:08:00
Module 02: Building your Vocabulary Part-01 00:02:00
Module 03: Building your Vocabulary Part-02 00:03:00
Module 04: Building your Vocabulary Part-03 00:07:00
Module 05: Building your Vocabulary Part-04 00:12:00
Module 06: Building your Vocabulary Part-05 00:06:00
Module 07: Dot Product 00:03:00
Module 08: Similarity using Dot Product 00:03:00
Module 09: Reducing Dimensions of your Vocabulary using token improvement 00:02:00
Module 10: Reducing Dimensions of your Vocabulary using n-grams 00:10:00
Module 11: Reducing Dimensions of your Vocabulary using normalizing 00:10:00
Module 12: Reducing Dimensions of your Vocabulary using case normalization 00:05:00
Module 13: When to use stemming and lemmatization? 00:04:00
Module 14: Sentiment Analysis Overview 00:05:00
Module 15: Two approaches for sentiment analysis 00:03:00
Module 16: Sentiment Analysis using rule-based 00:05:00
Module 17: Sentiment Analysis using machine learning – 1 00:10:00
Module 18: Sentiment Analysis using machine learning – 2 00:04:00
Module 19: Summary 00:01:00
Unit 05: Word2Vec in Detail and what is going on under the hood
Module 01: Introduction 00:04:00
Module 02: Bag of words in detail 00:14:00
Module 03: Vectorizing 00:08:00
Module 04: Vectorizing and Cosine Similarity 00:11:00
Module 05: Topic modeling in Detail 00:16:00
Module 06: Make your Vectors will more reflect the Meaning, or Topic, of the Document 00:10:00
Module 07: Sklearn in a short way 00:03:00
Module 08: Summary 00:02:00
Unit 06: Find and Represent the Meaning or Topic of Natural Language Text
Module 01: Keyword Search VS Semantic Search 00:04:00
Module 02: Problems in TI-IDF leads to Semantic Search 00:10:00
Module 03: Transform TF-IDF Vectors to Topic Vectors under the hood 00:11:00

U&P AI - Natural Language Processing with Python

4.9 ( 7 REVIEWS )
259 STUDENTS
$ 249.00
U&P AI - Natural Language Processing with Python
  • Course Highlights

Be efficient in Python programming & boost your skills with the U&P AI – Natural Language Processing with Python course. This course has been specially designed to help learners gain a good command of U&P AI – Natural Language Processing with Python, providing them with a solid foundation of knowledge to become a qualified professional.

With this course, containing on-demand video lectures and downloadable resources and affordable premium-quality E-learning content, you can learn at your own pace. The U&P AI – Natural Language Processing with Python covers the NPL, WordNet, Word2Vec applications which will allow you to enhance your CV, impress potential employers, and stand out from the crowd. The course will equip you with everything you need to succeed.

If you are looking for up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the tech industry, this is the right place. Enrol in U&P AI – Natural Language Processing with Python course today and learn from the very best the industry has to offer!

  • Learning outcome
  • Gain ideas about NLP and its applications
  • Familiar yourself with Feature Engineering
  • Learn about Corpuses & Frequency Distribution
  • Understand the WordNet and Word2Vec
  • Learn how to create vocabulary for any NLP Model
  • Explore and represent the Topic of Natural Language Text
  • Requirements
  • No formal qualifications required, anyone from any academic background can take this course.
  • Access to any internet-enabled smart device.
  • Why should I take this course?
  • 6+ hours of on-demand video lectures and downloadable resources.
  • Affordable premium-quality E-learning content, you can learn at your own pace.
  • You will receive a completion certificate upon completing the course.
  • Internationally recognized Accredited Qualification will boost up your resume.
  • You will learn the researched and proven approach adopted by successful salespeople to transform their careers.
  • You will be able to incorporate various practical sales techniques successfully and understand your customers better.
  • Who is This Course for
  • Ambitious learners who have already worked in the programming sector
  • Individuals who have the enthusiasm to obtain a new skill

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