| 001 Article Spinning - Problem Description.mp4 | 41.9 MB | ||
| 001 Article Spinning - Problem Description_en.srt | 10.8 KB | ||
| 001 Colab Notebooks.html | 614.4 B | ||
| 001 Introduction and Outline.mp4 | 73 MB | ||
| 001 Introduction and Outline_en.srt | 15.5 KB | ||
| 001 Machine Learning Models (Introduction).mp4 | 23.4 MB | ||
| 001 Machine Learning Models (Introduction)_en.srt | 6.2 KB | ||
| 001 Markov Models Section Introduction.mp4 | 13.1 MB | ||
| 001 Markov Models Section Introduction_en.srt | 3.5 KB | ||
| 001 Probabilistic Models (Introduction).mp4 | 26.9 MB | ||
| 001 Probabilistic Models (Introduction)_en.srt | 6.3 KB | ||
| 001 Section Introduction.mp4 | 26.3 MB | ||
| 001 Section Introduction_en.srt | 6.7 KB | ||
| 001 Sentiment Analysis - Problem Description.mp4 | 42.7 MB | ||
| 001 Sentiment Analysis - Problem Description_en.srt | 9.8 KB | ||
| 001 Spam Detection - Problem Description.mp4 | 31.3 MB | ||
| 001 Spam Detection - Problem Description_en.srt | 8.7 KB | ||
| 001 Vector Models & Text Preprocessing Intro.mp4 | 17.5 MB | ||
| 001 Vector Models & Text Preprocessing Intro_en.srt | 5 KB | ||
| 002 Article Spinning - N-Gram Approach.mp4 | 15.9 MB | ||
| 002 Article Spinning - N-Gram Approach_en.srt | 5.2 KB | ||
| 002 Basic Definitions for NLP.mp4 | 28.4 MB | ||
| 002 Basic Definitions for NLP_en.srt | 6.7 KB | ||
| 002 Ciphers.mp4 | 17.2 MB | ||
| 002 Ciphers_en.srt | 4.8 KB | ||
| 002 Logistic Regression Intuition (pt 1).mp4 | 63.6 MB | ||
| 002 Logistic Regression Intuition (pt 1)_en.srt | 22.5 KB | ||
| 002 Naive Bayes Intuition.mp4 | 51.3 MB | ||
| 002 Naive Bayes Intuition_en.srt | 15.2 KB | ||
| 002 The Markov Property.mp4 | 32.2 MB | ||
| 002 The Markov Property_en.srt | 9.5 KB | ||
| 002 Where to get the Code.mp4 | 62.9 MB | ||
| 002 Where to get the Code_en.srt | 15.6 KB | ||
| 003 Are You Beginner, Intermediate, or Advanced All are OK!.mp4 | 26.7 MB | ||
| 003 Are You Beginner, Intermediate, or Advanced All are OK!_en.srt | 7.2 KB | ||
| 003 Article Spinner Exercise Prompt.mp4 | 24.6 MB | ||
| 003 Article Spinner Exercise Prompt_en.srt | 7.6 KB | ||
| 003 Language Models (Review).mp4 | 65.5 MB | ||
| 003 Language Models (Review)_en.srt | 20.5 KB | ||
| 003 Multiclass Logistic Regression (pt 2).mp4 | 23.6 MB | ||
| 003 Multiclass Logistic Regression (pt 2)_en.srt | 8.5 KB | ||
| 003 Spam Detection - Exercise Prompt.mp4 | 8.7 MB | ||
| 003 Spam Detection - Exercise Prompt_en.srt | 2.6 KB | ||
| 003 The Markov Model.mp4 | 45.3 MB | ||
| 003 The Markov Model_en.srt | 16 KB | ||
| 003 What is a Vector.mp4 | 48.9 MB | ||
| 003 What is a Vector_en.srt | 14.9 KB | ||
| 004 Article Spinner in Python (pt 1).mp4 | 95.9 MB | ||
| 004 Article Spinner in Python (pt 1)_en.srt | 20.7 KB | ||
| 004 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 | 60.2 MB | ||
| 004 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1)_en.srt | 16.8 KB | ||
| 004 Bag of Words.mp4 | 13.9 MB | ||
| 004 Bag of Words_en.srt | 3.2 KB | ||
| 004 Genetic Algorithms.mp4 | 105.2 MB | ||
| 004 Genetic Algorithms_en.srt | 29.2 KB | ||
| 004 Logistic Regression Training and Interpretation (pt 3).mp4 | 39.6 MB | ||
| 004 Logistic Regression Training and Interpretation (pt 3)_en.srt | 10.8 KB | ||
| 004 Probability Smoothing and Log-Probabilities.mp4 | 32.9 MB | ||
| 004 Probability Smoothing and Log-Probabilities_en.srt | 10.3 KB | ||
| 005 Article Spinner in Python (pt 2).mp4 | 75.4 MB | ||
| 005 Article Spinner in Python (pt 2)_en.srt | 12.4 KB | ||
| 005 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 | 27.3 MB | ||
| 005 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2)_en.srt | 14.5 KB | ||
| 005 Building a Text Classifier (Theory).mp4 | 28.9 MB | ||
| 005 Building a Text Classifier (Theory)_en.srt | 9.5 KB | ||
| 005 Code Preparation.mp4 | 20.6 MB | ||
| 005 Code Preparation_en.srt | 6.7 KB | ||
| 005 Count Vectorizer (Theory).mp4 | 57.4 MB | ||
| 005 Count Vectorizer (Theory)_en.srt | 19.2 KB | ||
| 005 Sentiment Analysis - Exercise Prompt.mp4 | 16.6 MB | ||
| 005 Sentiment Analysis - Exercise Prompt_en.srt | 5.1 KB | ||
| 006 Building a Text Classifier (Exercise Prompt).mp4 | 16.1 MB | ||
| 006 Building a Text Classifier (Exercise Prompt)_en.srt | 8.8 KB | ||
| 006 Case Study Article Spinning Gone Wrong.mp4 | 28.2 MB | ||
| 006 Case Study Article Spinning Gone Wrong_en.srt | 7.6 KB | ||
| 006 Code pt 1.mp4 | 16 MB | ||
| 006 Code pt 1_en.srt | 4.1 KB | ||
| 006 Sentiment Analysis in Python (pt 1).mp4 | 24.8 MB | ||
| 006 Sentiment Analysis in Python (pt 1)_en.srt | 11.6 KB | ||
| 006 Spam Detection in Python.mp4 | 107.6 MB | ||
| 006 Spam Detection in Python_en.srt | 19.3 KB | ||
| 006 Tokenization.mp4 | 73.5 MB | ||
| 006 Tokenization_en.srt | 19.8 KB | ||
| 007 Building a Text Classifier (Code pt 1).mp4 | 57.7 MB | ||
| 007 Building a Text Classifier (Code pt 1)_en.srt | 11.8 KB | ||
| 007 Code pt 2.mp4 | 39.1 MB | ||
| 007 Code pt 2_en.srt | 9.3 KB | ||
| 007 Sentiment Analysis in Python (pt 2).mp4 | 52 MB | ||
| 007 Sentiment Analysis in Python (pt 2)_en.srt | 9.7 KB | ||
| 007 Stopwords.mp4 | 13.1 MB | ||
| 007 Stopwords_en.srt | 6.2 KB | ||
| 008 Building a Text Classifier (Code pt 2).mp4 | 72.2 MB | ||
| 008 Building a Text Classifier (Code pt 2)_en.srt | 13.8 KB | ||
| 008 Code pt 3.mp4 | 29.5 MB | ||
| 008 Code pt 3_en.srt | 6.1 KB | ||
| 008 Stemming and Lemmatization.mp4 | 57.9 MB | ||
| 008 Stemming and Lemmatization_en.srt | 15.8 KB | ||
| 009 Code pt 4.mp4 | 25.6 MB | ||
| 009 Code pt 4_en.srt | 4.8 KB | ||
| 009 Language Model (Theory).mp4 | 45 MB | ||
| 009 Language Model (Theory)_en.srt | 13.3 KB | ||
| 009 Stemming and Lemmatization Demo.mp4 | 74.8 MB | ||
| 009 Stemming and Lemmatization Demo_en.srt | 13.9 KB | ||
| 010 Code pt 5.mp4 | 41 MB | ||
| 010 Code pt 5_en.srt | 8.8 KB | ||
| 010 Count Vectorizer (Code).mp4 | 102 MB | ||
| 010 Count Vectorizer (Code)_en.srt | 19.1 KB | ||
| 010 Language Model (Exercise Prompt).mp4 | 28.8 MB | ||
| 010 Language Model (Exercise Prompt)_en.srt | 9 KB | ||
| 011 Code pt 6.mp4 | 13.3 MB | ||
| 011 Code pt 6_en.srt | 7.2 KB | ||
| 011 Language Model (Code pt 1).mp4 | 62.8 MB | ||
| 011 Language Model (Code pt 1)_en.srt | 13.2 KB | ||
| 011 Vector Similarity.mp4 | 45.1 MB | ||
| 011 Vector Similarity_en.srt | 15.2 KB | ||
| 012 Language Model (Code pt 2).mp4 | 52.4 MB | ||
| 012 Language Model (Code pt 2)_en.srt | 11.3 KB | ||
| 012 Section Conclusion.mp4 | 24.2 MB | ||
| 012 Section Conclusion_en.srt | 8.3 KB | ||
| 012 TF-IDF (Theory).mp4 | 58.6 MB | ||
| 012 TF-IDF (Theory)_en.srt | 18.3 KB | ||
| 013 (Interactive) Recommender Exercise Prompt.mp4 | 13.4 MB | ||
| 013 (Interactive) Recommender Exercise Prompt_en.srt | 3.2 KB | ||
| 013 Markov Models Section Summary.mp4 | 15.6 MB | ||
| 013 Markov Models Section Summary_en.srt | 4 KB | ||
| 014 TF-IDF (Code).mp4 | 124.9 MB | ||
| 014 TF-IDF (Code)_en.srt | 24.8 KB | ||
| 015 Word-to-Index Mapping.mp4 | 47.6 MB | ||
| 015 Word-to-Index Mapping_en.srt | 14.8 KB | ||
| 016 How to Build TF-IDF From Scratch.mp4 | 79.8 MB | ||
| 016 How to Build TF-IDF From Scratch_en.srt | 18.6 KB | ||
| 017 Neural Word Embeddings.mp4 | 45.5 MB | ||
| 017 Neural Word Embeddings_en.srt | 13.5 KB | ||
| 018 Neural Word Embeddings Demo.mp4 | 66.8 MB | ||
| 018 Neural Word Embeddings Demo_en.srt | 12.7 KB | ||
| 019 Vector Models & Text Preprocessing Summary.mp4 | 20.9 MB | ||
| 019 Vector Models & Text Preprocessing Summary_en.srt | 4.8 KB | ||
| [CourseClub.ME].url | 102.4 B | ||
| [CourseClub.Me].url | 102.4 B | ||
| [GigaCourse.Com].url | 0 B | ||
| external-assets-links.txt | 204.8 B | ||
| ▲ 148 total files | |||
Machine Learning: Natural Language Processing in Python (V2)
NLP: Use Markov Models, NLTK, Artificial Intelligence, Deep Learning, Machine Learning, and Data Science in Python
Created by Lazy Programmer Team, Lazy Programmer Inc.
Last updated 1/2022
English
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