English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 5h 24m | 0.99 GB
Bruno Gonçalves is a senior data scientist in the area of complex systems, human behavior, and finance. He has been programming in Python since 2005. For more than ten years, his work has focused on analyzing large-scale social media datasets for the temporal analysis of social behavior.
Table of Contents
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 Working with 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 Natural
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
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