Natural Language Processing
.MP4, AVC, 3400 kbps, 1280x720 | English, AAC, 192 kbps, 2 Ch | 2h 21m | 4.13 GB
Instructor: Bruno Goncalves
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Introduction
Lesson 1: Text Representations
Learning objectives
1.1 Represent words and numbers
1.2 Use one-hot encoding
1.3 Implement bag-of-words
1.4 Apply stop words
1.5 Understand TF/IDF
1.6 Understand stemming
Lesson 2: Topic Modeling
Learning objectives
2.1 Find topics in documents
2.2 Perform explicit semantic analysis
2.3 Implement document clustering
2.4 Implement Latent Semantic Analysis
2.5 Understand non-negative matrix factorization
Lesson 3: Sentiment Analysis
Learning objectives
3.1 Quantify words and feelings
3.2 Use negations and modifiers
3.3 Use corpus-based approaches
Lesson 4: Applications
Learning objectives
4.1 Understand word2vec word embeddings
4.2 Define GloVe
4.3 Apply language detection
Summary
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