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Language:
English
Total Size:
6.7 GB
Info Hash:
BE261FE5DA17AC84A4A3103CABB3C8D871AC10B9
Added By:
Added:
July 5, 2023, 9:42 p.m.
Stats:
|
(Last updated: Oct. 10, 2026, 7:28 p.m.)
| File | Size |
|---|---|
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. Introduction and Outline.mp4 | 73.0 MB |
| 1. Introduction and Outline.srt | 15.5 KB |
| 2. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 | 26.7 MB |
| 2. Are You Beginner, Intermediate, or Advanced All are OK!.srt | 7.2 KB |
| 1. Sentiment Analysis - Problem Description.mp4 | 42.7 MB |
| 1. Sentiment Analysis - Problem Description.srt | 9.8 KB |
| 2. Logistic Regression Intuition (pt 1).mp4 | 63.6 MB |
| 2. Logistic Regression Intuition (pt 1).srt | 22.5 KB |
| 3. Multiclass Logistic Regression (pt 2).mp4 | 23.6 MB |
| 3. Multiclass Logistic Regression (pt 2).srt | 8.5 KB |
| 4. Logistic Regression Training and Interpretation (pt 3).mp4 | 39.6 MB |
| 4. Logistic Regression Training and Interpretation (pt 3).srt | 10.8 KB |
| 5. Sentiment Analysis - Exercise Prompt.mp4 | 16.6 MB |
| 5. Sentiment Analysis - Exercise Prompt.srt | 5.1 KB |
| 6. Sentiment Analysis in Python (pt 1).mp4 | 63.1 MB |
| 6. Sentiment Analysis in Python (pt 1).srt | 11.6 KB |
| 7. Sentiment Analysis in Python (pt 2).mp4 | 52.0 MB |
| 7. Sentiment Analysis in Python (pt 2).srt | 9.7 KB |
| 1. Text Summarization Section Introduction.mp4 | 25.8 MB |
| 1. Text Summarization Section Introduction.srt | 7.5 KB |
| 10. Text Summarization Section Summary.mp4 | 20.1 MB |
| 10. Text Summarization Section Summary.srt | 4.4 KB |
| 2. Text Summarization Using Vectors.mp4 | 25.8 MB |
| 2. Text Summarization Using Vectors.srt | 7.3 KB |
| 3. Text Summarization Exercise Prompt.mp4 | 8.1 MB |
| 3. Text Summarization Exercise Prompt.srt | 2.3 KB |
| 4. Text Summarization in Python.mp4 | 78.2 MB |
| 4. Text Summarization in Python.srt | 15.0 KB |
| 5. TextRank Intuition.mp4 | 45.9 MB |
| 5. TextRank Intuition.srt | 10.9 KB |
| 6. TextRank - How It Really Works (Advanced).mp4 | 49.3 MB |
| 6. TextRank - How It Really Works (Advanced).srt | 13.5 KB |
| 7. TextRank Exercise Prompt (Advanced).mp4 | 7.5 MB |
| 7. TextRank Exercise Prompt (Advanced).srt | 1.7 KB |
| 8. TextRank in Python (Advanced).mp4 | 82.3 MB |
| 8. TextRank in Python (Advanced).srt | 17.1 KB |
| 9. Text Summarization in Python - The Easy Way (Beginner).mp4 | 45.2 MB |
| 9. Text Summarization in Python - The Easy Way (Beginner).srt | 7.8 KB |
| 1. Topic Modeling Section Introduction.mp4 | 17.0 MB |
| 1. Topic Modeling Section Introduction.srt | 4.1 KB |
| 2. Latent Dirichlet Allocation (LDA) - Essentials.mp4 | 55.2 MB |
| 2. Latent Dirichlet Allocation (LDA) - Essentials.srt | 15.2 KB |
| 3. LDA - Code Preparation.mp4 | 14.5 MB |
| 3. LDA - Code Preparation.srt | 4.9 KB |
| 4. LDA - Maybe Useful Picture (Optional).mp4 | 9.0 MB |
| 4. LDA - Maybe Useful Picture (Optional).srt | 2.5 KB |
| 5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 | 60.2 MB |
| 5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).srt | 20.2 KB |
| 6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 | 72.4 MB |
| 6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.srt | 13.3 KB |
| 7. Non-Negative Matrix Factorization (NMF) Intuition.mp4 | 52.5 MB |
| 7. Non-Negative Matrix Factorization (NMF) Intuition.srt | 13.8 KB |
| 8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 | 36.0 MB |
| 8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.srt | 4.9 KB |
| 9. Topic Modeling Section Summary.mp4 | 9.8 MB |
| 9. Topic Modeling Section Summary.srt | 2.0 KB |
| 1. LSA LSI Section Introduction.mp4 | 21.0 MB |
| 1. LSA LSI Section Introduction.srt | 5.2 KB |
| 2. SVD (Singular Value Decomposition) Intuition.mp4 | 81.8 MB |
| 2. SVD (Singular Value Decomposition) Intuition.srt | 15.4 KB |
| 3. LSA LSI Applying SVD to NLP.mp4 | 34.4 MB |
| 3. LSA LSI Applying SVD to NLP.srt | 10.3 KB |
| 4. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 | 57.6 MB |
| 4. Latent Semantic Analysis Latent Semantic Indexing in Python.srt | 10.1 KB |
| 5. LSA LSI Exercises.mp4 | 29.1 MB |
| 5. LSA LSI Exercises.srt | 7.3 KB |
| 1. Deep Learning Introduction (Intermediate-Advanced).mp4 | 24.5 MB |
| 1. Deep Learning Introduction (Intermediate-Advanced).srt | 6.8 KB |
| 1. The Neuron - Section Introduction.mp4 | 11.0 MB |
| 1. The Neuron - Section Introduction.srt | 2.9 KB |
| 2. Fitting a Line.mp4 | 68.6 MB |
| 2. Fitting a Line.srt | 18.4 KB |
| 3. Classification Code Preparation.mp4 | 32.9 MB |
| 3. Classification Code Preparation.srt | 9.5 KB |
| 4. Text Classification in Tensorflow.mp4 | 81.7 MB |
| 4. Text Classification in Tensorflow.srt | 11.7 KB |
| 5. The Neuron.mp4 | 45.3 MB |
| 5. The Neuron.srt | 12.7 KB |
| 6. How does a model learn.mp4 | 51.6 MB |
| 6. How does a model learn.srt | 14.4 KB |
| 7. The Neuron - Section Summary.mp4 | 10.3 MB |
| 7. The Neuron - Section Summary.srt | 2.2 KB |
| 1. ANN - Section Introduction.mp4 | 38.6 MB |
| 1. ANN - Section Introduction.srt | 9.3 KB |
| 10. Embeddings.mp4 | 42.3 MB |
| 10. Embeddings.srt | 12.6 KB |
| 11. CBOW (Advanced).mp4 | 15.8 MB |
| 11. CBOW (Advanced).srt | 5.2 KB |
| 12. CBOW Exercise Prompt.mp4 | 5.0 MB |
| 12. CBOW Exercise Prompt.srt | 970 bytes |
| 13. CBOW in Tensorflow (Advanced).mp4 | 117.6 MB |
| 13. CBOW in Tensorflow (Advanced).srt | 20.3 KB |
| 14. ANN - Section Summary.mp4 | 7.6 MB |
| 14. ANN - Section Summary.srt | 1.9 KB |
| 15. Aside How to Choose Hyperparameters (Optional).mp4 | 38.1 MB |
| 15. Aside How to Choose Hyperparameters (Optional).srt | 8.6 KB |
| 2. Forward Propagation.mp4 | 46.7 MB |
| 2. Forward Propagation.srt | 12.6 KB |
| 3. The Geometrical Picture.mp4 | 56.5 MB |
| 3. The Geometrical Picture.srt | 11.8 KB |
| 4. Activation Functions.mp4 | 89.3 MB |
| 4. Activation Functions.srt | 22.9 KB |
| 5. Multiclass Classification.mp4 | 44.4 MB |
| 5. Multiclass Classification.srt | 11.3 KB |
| 6. ANN Code Preparation.mp4 | 20.2 MB |
| 6. ANN Code Preparation.srt | 6.0 KB |
| 7. Text Classification ANN in Tensorflow.mp4 | 36.1 MB |
| 7. Text Classification ANN in Tensorflow.srt | 5.0 KB |
| 8. Text Preprocessing Code Preparation.mp4 | 50.0 MB |
| 8. Text Preprocessing Code Preparation.srt | 14.9 KB |
| 9. Text Preprocessing in Tensorflow.mp4 | 30.9 MB |
| 9. Text Preprocessing in Tensorflow.srt | 6.3 KB |
| 1. CNN - Section Introduction.mp4 | 25.6 MB |
| 1. CNN - Section Introduction.srt | 5.9 KB |
| 2. What is Convolution.mp4 | 79.9 MB |
| 2. What is Convolution.srt | 20.7 KB |
| 3. What is Convolution (Pattern Matching).mp4 | 24.6 MB |
| 3. What is Convolution (Pattern Matching).srt | 6.9 KB |
| 4. What is Convolution (Weight Sharing).mp4 | 29.8 MB |
| 4. What is Convolution (Weight Sharing).srt | 8.1 KB |
| 5. Convolution on Color Images.mp4 | 75.2 MB |
| 5. Convolution on Color Images.srt | 20.9 KB |
| 6. CNN Architecture.mp4 | 89.3 MB |
| 6. CNN Architecture.srt | 28.8 KB |
| 7. CNNs for Text.mp4 | 40.5 MB |
| 7. CNNs for Text.srt | 9.8 KB |
| 8. Convolutional Neural Network for NLP in Tensorflow.mp4 | 42.0 MB |
| 8. Convolutional Neural Network for NLP in Tensorflow.srt | 5.0 KB |
| 9. CNN - Section Summary.mp4 | 8.2 MB |
| 9. CNN - Section Summary.srt | 1.7 KB |
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. RNN - Section Introduction.mp4 | 20.9 MB |
| 1. RNN - Section Introduction.srt | 6.3 KB |
| 10. Named Entity Recognition (NER) in Tensorflow.mp4 | 31.5 MB |
| 10. Named Entity Recognition (NER) in Tensorflow.srt | 6.1 KB |
| 11. Exercise Return to CNNs (Advanced).mp4 | 14.6 MB |
| 11. Exercise Return to CNNs (Advanced).srt | 4.1 KB |
| 12. RNN - Section Summary.mp4 | 9.1 MB |
| 12. RNN - Section Summary.srt | 2.3 KB |
| 2. Simple RNN Elman Unit (pt 1).mp4 | 40.8 MB |
| 2. Simple RNN Elman Unit (pt 1).srt | 11.6 KB |
| 3. Simple RNN Elman Unit (pt 2).mp4 | 41.2 MB |
| 3. Simple RNN Elman Unit (pt 2).srt | 12.9 KB |
| 4. RNN Code Preparation.mp4 | 42.1 MB |
| 4. RNN Code Preparation.srt | 12.6 KB |
| 5. RNNs Paying Attention to Shapes.mp4 | 57.2 MB |
| 5. RNNs Paying Attention to Shapes.srt | 10.2 KB |
| 6. GRU and LSTM (pt 1).mp4 | 82.3 MB |
| 6. GRU and LSTM (pt 1).srt | 23.3 KB |
| 7. GRU and LSTM (pt 2).mp4 | 50.3 MB |
| 7. GRU and LSTM (pt 2).srt | 15.1 KB |
| 8. RNN for Text Classification in Tensorflow.mp4 | 45.9 MB |
| 8. RNN for Text Classification in Tensorflow.srt | 5.6 KB |
| 9. Parts-of-Speech (POS) Tagging in Tensorflow.mp4 | 145.1 MB |
| 9. Parts-of-Speech (POS) Tagging in Tensorflow.srt | 22.6 KB |
| 1. Pre-Installation Check.mp4 | 22.8 MB |
| 1. Pre-Installation Check.srt | 6.6 KB |
| 2. Anaconda Environment Setup.mp4 | 52.6 MB |
| 2. Anaconda Environment Setup.srt | 20.1 KB |
| 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 | 50.9 MB |
| 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt | 14.6 KB |
| 1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 | 43.6 MB |
| 1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt | 12.0 KB |
| 1.1 Data Links.html | 157 bytes |
| 1.2 Github Link.html | 139 bytes |
| 2. How to use Github & Extra Coding Tips (Optional).mp4 | 63.9 MB |
| 2. How to use Github & Extra Coding Tips (Optional).srt | 15.7 KB |
| 3. Where to get the code, notebooks, and data.mp4 | 17.7 MB |
| 3. Where to get the code, notebooks, and data.srt | 4.3 KB |
| 3.1 Code Link.html | 125 bytes |
| 3.2 Data Links.html | 157 bytes |
| 3.3 Github Link.html | 139 bytes |
| 4. How to Succeed in This Course.mp4 | 41.2 MB |
| 4. How to Succeed in This Course.srt | 13.0 KB |
| 5. Temporary 403 Errors.mp4 | 22.0 MB |
| 5. Temporary 403 Errors.srt | 3.7 KB |
| 1. How to Code by Yourself (part 1).mp4 | 71.9 MB |
| 1. How to Code by Yourself (part 1).srt | 22.7 KB |
| 2. How to Code by Yourself (part 2).mp4 | 49.2 MB |
| 2. How to Code by Yourself (part 2).srt | 13.3 KB |
| 3. Proof that using Jupyter Notebook is the same as not using it.mp4 | 69.4 MB |
| 3. Proof that using Jupyter Notebook is the same as not using it.srt | 14.3 KB |
| 1. How to Succeed in this Course (Long Version).mp4 | 17.9 MB |
| 1. How to Succeed in this Course (Long Version).srt | 14.5 KB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 39.0 MB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt | 32.4 KB |
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 | 79.7 MB |
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt | 16.6 KB |
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 | 108.1 MB |
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt | 23.6 KB |
| 1. What is the Appendix.mp4 | 16.4 MB |
| 1. What is the Appendix.srt | 3.8 KB |
| 2. BONUS.mp4 | 39.8 MB |
| 2. BONUS.srt | 7.9 KB |
| 1. Vector Models & Text Preprocessing Intro.mp4 | 17.5 MB |
| 1. Vector Models & Text Preprocessing Intro.srt | 5.0 KB |
| 10. Count Vectorizer (Code).mp4 | 102.0 MB |
| 10. Count Vectorizer (Code).srt | 19.1 KB |
| 11. Vector Similarity.mp4 | 45.1 MB |
| 11. Vector Similarity.srt | 15.2 KB |
| 12. TF-IDF (Theory).mp4 | 58.6 MB |
| 12. TF-IDF (Theory).srt | 18.3 KB |
| 13. (Interactive) Recommender Exercise Prompt.mp4 | 13.4 MB |
| 13. (Interactive) Recommender Exercise Prompt.srt | 3.2 KB |
| 14. TF-IDF (Code).mp4 | 124.9 MB |
| 14. TF-IDF (Code).srt | 24.8 KB |
| 15. Word-to-Index Mapping.mp4 | 47.6 MB |
| 15. Word-to-Index Mapping.srt | 14.8 KB |
| 16. How to Build TF-IDF From Scratch.mp4 | 79.8 MB |
| 16. How to Build TF-IDF From Scratch.srt | 18.6 KB |
| 17. Neural Word Embeddings.mp4 | 45.5 MB |
| 17. Neural Word Embeddings.srt | 13.5 KB |
| 18. Neural Word Embeddings Demo.mp4 | 66.8 MB |
| 18. Neural Word Embeddings Demo.srt | 12.7 KB |
| 19. Vector Models & Text Preprocessing Summary.mp4 | 20.9 MB |
| 19. Vector Models & Text Preprocessing Summary.srt | 4.8 KB |
| 2. Basic Definitions for NLP.mp4 | 28.4 MB |
| 2. Basic Definitions for NLP.srt | 6.7 KB |
| 20. Text Summarization Preview.mp4 | 6.3 MB |
| 20. Text Summarization Preview.srt | 1.7 KB |
| 21. How To Do NLP In Other Languages.mp4 | 56.0 MB |
| 21. How To Do NLP In Other Languages.srt | 14.6 KB |
| 22. Suggestion Box.mp4 | 27.2 MB |
| 22. Suggestion Box.srt | 4.7 KB |
| 3. What is a Vector.mp4 | 48.9 MB |
| 3. What is a Vector.srt | 14.8 KB |
| 4. Bag of Words.mp4 | 13.9 MB |
| 4. Bag of Words.srt | 3.2 KB |
| 5. Count Vectorizer (Theory).mp4 | 57.4 MB |
| 5. Count Vectorizer (Theory).srt | 19.2 KB |
| 6. Tokenization.mp4 | 73.5 MB |
| 6. Tokenization.srt | 19.8 KB |
| 7. Stopwords.mp4 | 23.4 MB |
| 7. Stopwords.srt | 6.3 KB |
| 8. Stemming and Lemmatization.mp4 | 57.9 MB |
| 8. Stemming and Lemmatization.srt | 15.8 KB |
| 9. Stemming and Lemmatization Demo.mp4 | 74.8 MB |
| 9. Stemming and Lemmatization Demo.srt | 13.9 KB |
| 1. Probabilistic Models (Introduction).mp4 | 26.9 MB |
| 1. Probabilistic Models (Introduction).srt | 6.3 KB |
| 1. Markov Models Section Introduction.mp4 | 13.1 MB |
| 1. Markov Models Section Introduction.srt | 3.5 KB |
| 10. Language Model (Exercise Prompt).mp4 | 28.8 MB |
| 10. Language Model (Exercise Prompt).srt | 9.0 KB |
| 11. Language Model (Code pt 1).mp4 | 62.8 MB |
| 11. Language Model (Code pt 1).srt | 13.2 KB |
| 12. Language Model (Code pt 2).mp4 | 52.4 MB |
| 12. Language Model (Code pt 2).srt | 11.3 KB |
| 13. Markov Models Section Summary.mp4 | 15.6 MB |
| 13. Markov Models Section Summary.srt | 4.0 KB |
| 2. The Markov Property.mp4 | 32.3 MB |
| 2. The Markov Property.srt | 9.4 KB |
| 3. The Markov Model.mp4 | 45.8 MB |
| 3. The Markov Model.srt | 16.5 KB |
| 4. Probability Smoothing and Log-Probabilities.mp4 | 34.1 MB |
| 4. Probability Smoothing and Log-Probabilities.srt | 10.3 KB |
| 5. Building a Text Classifier (Theory).mp4 | 28.9 MB |
| 5. Building a Text Classifier (Theory).srt | 9.4 KB |
| 6. Building a Text Classifier (Exercise Prompt).mp4 | 29.4 MB |
| 6. Building a Text Classifier (Exercise Prompt).srt | 8.8 KB |
| 7. Building a Text Classifier (Code pt 1).mp4 | 57.7 MB |
| 7. Building a Text Classifier (Code pt 1).srt | 11.8 KB |
| 8. Building a Text Classifier (Code pt 2).mp4 | 72.2 MB |
| 8. Building a Text Classifier (Code pt 2).srt | 13.8 KB |
| 9. Language Model (Theory).mp4 | 45.0 MB |
| 9. Language Model (Theory).srt | 13.3 KB |
| [CourseClub.Me].url | 122 bytes |
| [FreeCourseSite.com].url | 127 bytes |
| [GigaCourse.Com].url | 49 bytes |
| 1. Article Spinning - Problem Description.mp4 | 41.9 MB |
| 1. Article Spinning - Problem Description.srt | 10.8 KB |
| 2. Article Spinning - N-Gram Approach.mp4 | 15.9 MB |
| 2. Article Spinning - N-Gram Approach.srt | 5.2 KB |
| 3. Article Spinner Exercise Prompt.mp4 | 24.6 MB |
| 3. Article Spinner Exercise Prompt.srt | 7.6 KB |
| 4. Article Spinner in Python (pt 1).mp4 | 95.9 MB |
| 4. Article Spinner in Python (pt 1).srt | 20.7 KB |
| 5. Article Spinner in Python (pt 2).mp4 | 75.4 MB |
| 5. Article Spinner in Python (pt 2).srt | 12.4 KB |
| 6. Case Study Article Spinning Gone Wrong.mp4 | 28.2 MB |
| 6. Case Study Article Spinning Gone Wrong.srt | 7.6 KB |
| 1. Section Introduction.mp4 | 26.3 MB |
| 1. Section Introduction.srt | 6.7 KB |
| 10. Code pt 5.mp4 | 41.0 MB |
| 10. Code pt 5.srt | 8.8 KB |
| 11. Code pt 6.mp4 | 39.4 MB |
| 11. Code pt 6.srt | 7.2 KB |
| 12. Cipher Decryption - Additional Discussion.mp4 | 14.7 MB |
| 12. Cipher Decryption - Additional Discussion.srt | 4.1 KB |
| 13. Section Conclusion.mp4 | 24.2 MB |
| 13. Section Conclusion.srt | 8.3 KB |
| 2. Ciphers.mp4 | 17.2 MB |
| 2. Ciphers.srt | 4.8 KB |
| 3. Language Models (Review).mp4 | 65.5 MB |
| 3. Language Models (Review).srt | 20.5 KB |
| 4. Genetic Algorithms.mp4 | 105.2 MB |
| 4. Genetic Algorithms.srt | 29.2 KB |
| 5. Code Preparation.mp4 | 20.6 MB |
| 5. Code Preparation.srt | 6.7 KB |
| 6. Code pt 1.mp4 | 16.0 MB |
| 6. Code pt 1.srt | 4.1 KB |
| 7. Code pt 2.mp4 | 39.1 MB |
| 7. Code pt 2.srt | 9.3 KB |
| 8. Code pt 3.mp4 | 29.5 MB |
| 8. Code pt 3.srt | 6.1 KB |
| 9. Code pt 4.mp4 | 25.6 MB |
| 9. Code pt 4.srt | 4.8 KB |
| 1. Machine Learning Models (Introduction).mp4 | 29.6 MB |
| 1. Machine Learning Models (Introduction).srt | 7.8 KB |
| 1. Spam Detection - Problem Description.mp4 | 31.3 MB |
| 1. Spam Detection - Problem Description.srt | 8.7 KB |
| 2. Naive Bayes Intuition.mp4 | 51.3 MB |
| 2. Naive Bayes Intuition.srt | 15.2 KB |
| 3. Spam Detection - Exercise Prompt.mp4 | 8.7 MB |
| 3. Spam Detection - Exercise Prompt.srt | 2.6 KB |
| 4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 | 60.2 MB |
| 4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).srt | 16.8 KB |
| 5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 | 54.0 MB |
| 5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).srt | 14.5 KB |
| 6. Spam Detection in Python.mp4 | 107.6 MB |
| 6. Spam Detection in Python.srt | 19.3 KB |
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2023-10-28
NOTE
SOURCE: Udemy Machine Learning Natural Language Processing in Python V2
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