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Natural Language Processing (NLP) Fundamentals, 3rd Edition

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Free Download Natural Language Processing (NLP) Fundamentals, 3rd Edition
ISBN: 9780135439692 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 6h 14m | 1.34 GB
Instructor: Bruno Goncalves

The Sneak Peek program provides early access to Pearson video products and is exclusively available to subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing.
Introduction
Natural Language Processing (NLP) Fundamentals: Introduction
Lesson 1: Text Representation
Topics
1.1 One-hot Encoding
1.2 Bag of Words
1.3 Stop Words
1.4 TF-IDF
1.5 N-grams
1.6 Word Embeddings
1.7 Demo
Lesson 2: Text Cleaning
Topics
2.1 Stemming
2.2 Lemmatization
2.3 Regular Expressions
2.4 Text Cleaning Demo
Lesson 3: Named Entity Recognition
Topics
3.1 Part of Speech Tagging
3.2 Chunking
3.3 Chinking
3.4 Named Entity Recognition
3.5 Demo
Lesson 4: Topic Modeling
Topics
4.1 Explicit Semantic Analysis
4.2 Document Clustering
4.3 Latent Semantic Analysis
4.4 LDA
4.5 Non-negative Matrix Factorization
4.6 Demo
Lesson 5: Sentiment Analysis
Topics
5.1 Quantify Words and Feelings
5.2 Negations and Modifiers
5.3 Corpus-based Approaches
5.4 Demo
Lesson 6: Text Classification
Topics
6.1 Feed Forward Networks
6.2 Convolutional Neural Networks
6.3 Applications
6.4 Demo
Lesson 7: Sequence Modeling
Topics
7.1 Recurrent Neural Networks
7.2 Gated Recurrent Unit
7.3 Long Short-term Memory
7.4 Auto-encoder Models
7.5 Demo
Lesson 8: Applications
Topics
8.1 Word2vec Embeddings
8.2 GloVe
8.3 Transfer Learning
8.4 Language Detection
8.5 Demo
Lesson 9: NLP with Large Language Models
Topics
9.1 Large Language Models
9.2 Transformers
9.3 BERT
9.4 HuggingFace
9.5 NLP Tasks
9.6 Demo
Summary
Natural Language Processing (NLP) Fundamentals: Summary
Code:
https://www.oreilly.com/library/view/natural-language-processing/9780135439692/
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