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[GigaCourse.Com] Udemy - Machine Learning Natural Language Processing in Python (V2)
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18. Recurrent Neural Networks
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9. Parts-of-Speech (POS) Tagging in Tensorflow.mp4 - 145.1 MB
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6. GRU and LSTM (pt 1).mp4 - 82.25 MB
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5. RNNs Paying Attention to Shapes.mp4 - 57.17 MB
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7. GRU and LSTM (pt 2).mp4 - 50.35 MB
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8. RNN for Text Classification in Tensorflow.mp4 - 45.91 MB
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4. RNN Code Preparation.mp4 - 42.14 MB
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3. Simple RNN Elman Unit (pt 2).mp4 - 41.18 MB
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2. Simple RNN Elman Unit (pt 1).mp4 - 40.83 MB
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10. Named Entity Recognition (NER) in Tensorflow.mp4 - 31.54 MB
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1. RNN - Section Introduction.mp4 - 20.91 MB
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11. Exercise Return to CNNs (Advanced).mp4 - 14.55 MB
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12. RNN - Section Summary.mp4 - 9.1 MB
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6. GRU and LSTM (pt 1).srt - 23.28 KB
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9. Parts-of-Speech (POS) Tagging in Tensorflow.srt - 22.62 KB
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7. GRU and LSTM (pt 2).srt - 15.11 KB
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3. Simple RNN Elman Unit (pt 2).srt - 12.91 KB
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4. RNN Code Preparation.srt - 12.58 KB
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2. Simple RNN Elman Unit (pt 1).srt - 11.56 KB
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5. RNNs Paying Attention to Shapes.srt - 10.2 KB
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1. RNN - Section Introduction.srt - 6.32 KB
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10. Named Entity Recognition (NER) in Tensorflow.srt - 6.12 KB
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8. RNN for Text Classification in Tensorflow.srt - 5.57 KB
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11. Exercise Return to CNNs (Advanced).srt - 4.11 KB
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12. RNN - Section Summary.srt - 2.31 KB
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3. Vector Models and Text Preprocessing
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14. TF-IDF (Code).mp4 - 124.92 MB
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10. Count Vectorizer (Code).mp4 - 101.99 MB
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16. How to Build TF-IDF From Scratch.mp4 - 79.8 MB
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9. Stemming and Lemmatization Demo.mp4 - 74.84 MB
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6. Tokenization.mp4 - 73.51 MB
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18. Neural Word Embeddings Demo.mp4 - 66.84 MB
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12. TF-IDF (Theory).mp4 - 58.57 MB
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8. Stemming and Lemmatization.mp4 - 57.92 MB
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5. Count Vectorizer (Theory).mp4 - 57.43 MB
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21. How To Do NLP In Other Languages.mp4 - 55.96 MB
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3. What is a Vector.mp4 - 48.94 MB
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15. Word-to-Index Mapping.mp4 - 47.58 MB
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17. Neural Word Embeddings.mp4 - 45.54 MB
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11. Vector Similarity.mp4 - 45.11 MB
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2. Basic Definitions for NLP.mp4 - 28.37 MB
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22. Suggestion Box.mp4 - 27.16 MB
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7. Stopwords.mp4 - 23.44 MB
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19. Vector Models & Text Preprocessing Summary.mp4 - 20.86 MB
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1. Vector Models & Text Preprocessing Intro.mp4 - 17.53 MB
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4. Bag of Words.mp4 - 13.86 MB
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13. (Interactive) Recommender Exercise Prompt.mp4 - 13.38 MB
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20. Text Summarization Preview.mp4 - 6.29 MB
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14. TF-IDF (Code).srt - 24.8 KB
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6. Tokenization.srt - 19.84 KB
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5. Count Vectorizer (Theory).srt - 19.18 KB
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10. Count Vectorizer (Code).srt - 19.13 KB
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16. How to Build TF-IDF From Scratch.srt - 18.56 KB
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12. TF-IDF (Theory).srt - 18.27 KB
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8. Stemming and Lemmatization.srt - 15.82 KB
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11. Vector Similarity.srt - 15.16 KB
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3. What is a Vector.srt - 14.85 KB
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15. Word-to-Index Mapping.srt - 14.8 KB
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21. How To Do NLP In Other Languages.srt - 14.56 KB
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9. Stemming and Lemmatization Demo.srt - 13.91 KB
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17. Neural Word Embeddings.srt - 13.48 KB
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18. Neural Word Embeddings Demo.srt - 12.74 KB
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2. Basic Definitions for NLP.srt - 6.66 KB
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7. Stopwords.srt - 6.31 KB
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1. Vector Models & Text Preprocessing Intro.srt - 4.99 KB
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19. Vector Models & Text Preprocessing Summary.srt - 4.79 KB
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22. Suggestion Box.srt - 4.75 KB
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13. (Interactive) Recommender Exercise Prompt.srt - 3.21 KB
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4. Bag of Words.srt - 3.15 KB
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20. Text Summarization Preview.srt - 1.67 KB
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16. Feedforward Artificial Neural Networks
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13. CBOW in Tensorflow (Advanced).mp4 - 117.56 MB
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4. Activation Functions.mp4 - 89.31 MB
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3. The Geometrical Picture.mp4 - 56.53 MB
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8. Text Preprocessing Code Preparation.mp4 - 49.99 MB
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2. Forward Propagation.mp4 - 46.72 MB
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5. Multiclass Classification.mp4 - 44.41 MB
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10. Embeddings.mp4 - 42.29 MB
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1. ANN - Section Introduction.mp4 - 38.63 MB
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15. Aside How to Choose Hyperparameters (Optional).mp4 - 38.07 MB
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7. Text Classification ANN in Tensorflow.mp4 - 36.12 MB
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9. Text Preprocessing in Tensorflow.mp4 - 30.93 MB
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6. ANN Code Preparation.mp4 - 20.14 MB
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11. CBOW (Advanced).mp4 - 15.78 MB
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14. ANN - Section Summary.mp4 - 7.6 MB
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12. CBOW Exercise Prompt.mp4 - 5.02 MB
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4. Activation Functions.srt - 22.92 KB
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13. CBOW in Tensorflow (Advanced).srt - 20.31 KB
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8. Text Preprocessing Code Preparation.srt - 14.87 KB
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10. Embeddings.srt - 12.63 KB
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2. Forward Propagation.srt - 12.59 KB
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3. The Geometrical Picture.srt - 11.78 KB
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5. Multiclass Classification.srt - 11.33 KB
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1. ANN - Section Introduction.srt - 9.32 KB
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15. Aside How to Choose Hyperparameters (Optional).srt - 8.56 KB
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9. Text Preprocessing in Tensorflow.srt - 6.3 KB
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6. ANN Code Preparation.srt - 5.98 KB
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11. CBOW (Advanced).srt - 5.23 KB
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7. Text Classification ANN in Tensorflow.srt - 5.03 KB
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14. ANN - Section Summary.srt - 1.91 KB
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12. CBOW Exercise Prompt.srt - 970 B
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22. Effective Learning Strategies for Machine Learning FAQ
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4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 - 108.15 MB
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3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 - 79.68 MB
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2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 - 38.96 MB
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1. How to Succeed in this Course (Long Version).mp4 - 17.88 MB
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2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt - 32.45 KB
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4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt - 23.61 KB
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3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt - 16.58 KB
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1. How to Succeed in this Course (Long Version).srt - 14.55 KB
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9. Spam Detection
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6. Spam Detection in Python.mp4 - 107.6 MB
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4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 - 60.21 MB
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5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 - 53.98 MB
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2. Naive Bayes Intuition.mp4 - 51.33 MB
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1. Spam Detection - Problem Description.mp4 - 31.33 MB
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3. Spam Detection - Exercise Prompt.mp4 - 8.73 MB
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6. Spam Detection in Python.srt - 19.27 KB
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4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).srt - 16.78 KB
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2. Naive Bayes Intuition.srt - 15.22 KB
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5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).srt - 14.46 KB
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1. Spam Detection - Problem Description.srt - 8.72 KB
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3. Spam Detection - Exercise Prompt.srt - 2.63 KB
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7. Cipher Decryption (Advanced)
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4. Genetic Algorithms.mp4 - 105.17 MB
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3. Language Models (Review).mp4 - 65.53 MB
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10. Code pt 5.mp4 - 40.97 MB
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11. Code pt 6.mp4 - 39.4 MB
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7. Code pt 2.mp4 - 39.13 MB
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8. Code pt 3.mp4 - 29.54 MB
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1. Section Introduction.mp4 - 26.33 MB
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9. Code pt 4.mp4 - 25.62 MB
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13. Section Conclusion.mp4 - 24.25 MB
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5. Code Preparation.mp4 - 20.63 MB
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2. Ciphers.mp4 - 17.22 MB
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6. Code pt 1.mp4 - 15.98 MB
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12. Cipher Decryption - Additional Discussion.mp4 - 14.7 MB
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4. Genetic Algorithms.srt - 29.21 KB
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3. Language Models (Review).srt - 20.51 KB
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7. Code pt 2.srt - 9.26 KB
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10. Code pt 5.srt - 8.82 KB
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13. Section Conclusion.srt - 8.29 KB
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11. Code pt 6.srt - 7.24 KB
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5. Code Preparation.srt - 6.74 KB
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1. Section Introduction.srt - 6.67 KB
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8. Code pt 3.srt - 6.15 KB
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9. Code pt 4.srt - 4.84 KB
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2. Ciphers.srt - 4.8 KB
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6. Code pt 1.srt - 4.14 KB
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12. Cipher Decryption - Additional Discussion.srt - 4.07 KB
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6. Article Spinner (Intermediate)
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4. Article Spinner in Python (pt 1).mp4 - 95.89 MB
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5. Article Spinner in Python (pt 2).mp4 - 75.37 MB
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1. Article Spinning - Problem Description.mp4 - 41.92 MB
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6. Case Study Article Spinning Gone Wrong.mp4 - 28.24 MB
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3. Article Spinner Exercise Prompt.mp4 - 24.63 MB
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2. Article Spinning - N-Gram Approach.mp4 - 15.92 MB
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4. Article Spinner in Python (pt 1).srt - 20.67 KB
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5. Article Spinner in Python (pt 2).srt - 12.41 KB
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1. Article Spinning - Problem Description.srt - 10.77 KB
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3. Article Spinner Exercise Prompt.srt - 7.57 KB
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6. Case Study Article Spinning Gone Wrong.srt - 7.55 KB
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2. Article Spinning - N-Gram Approach.srt - 5.21 KB
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17. Convolutional Neural Networks
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6. CNN Architecture.mp4 - 89.28 MB
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2. What is Convolution.mp4 - 79.86 MB
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5. Convolution on Color Images.mp4 - 75.19 MB
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8. Convolutional Neural Network for NLP in Tensorflow.mp4 - 42.04 MB
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7. CNNs for Text.mp4 - 40.48 MB
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4. What is Convolution (Weight Sharing).mp4 - 29.81 MB
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1. CNN - Section Introduction.mp4 - 25.62 MB
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3. What is Convolution (Pattern Matching).mp4 - 24.63 MB
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9. CNN - Section Summary.mp4 - 8.2 MB
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6. CNN Architecture.srt - 28.76 KB
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5. Convolution on Color Images.srt - 20.93 KB
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2. What is Convolution.srt - 20.66 KB
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7. CNNs for Text.srt - 9.76 KB
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4. What is Convolution (Weight Sharing).srt - 8.07 KB
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3. What is Convolution (Pattern Matching).srt - 6.94 KB
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1. CNN - Section Introduction.srt - 5.95 KB
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8. Convolutional Neural Network for NLP in Tensorflow.srt - 5.03 KB
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9. CNN - Section Summary.srt - 1.67 KB
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11. Text Summarization
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8. TextRank in Python (Advanced).mp4 - 82.3 MB
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4. Text Summarization in Python.mp4 - 78.16 MB
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6. TextRank - How It Really Works (Advanced).mp4 - 49.32 MB
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5. TextRank Intuition.mp4 - 45.93 MB
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9. Text Summarization in Python - The Easy Way (Beginner).mp4 - 45.17 MB
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2. Text Summarization Using Vectors.mp4 - 25.77 MB
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1. Text Summarization Section Introduction.mp4 - 25.75 MB
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10. Text Summarization Section Summary.mp4 - 20.1 MB
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3. Text Summarization Exercise Prompt.mp4 - 8.11 MB
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7. TextRank Exercise Prompt (Advanced).mp4 - 7.47 MB
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8. TextRank in Python (Advanced).srt - 17.1 KB
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4. Text Summarization in Python.srt - 15.01 KB
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6. TextRank - How It Really Works (Advanced).srt - 13.52 KB
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5. TextRank Intuition.srt - 10.91 KB
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9. Text Summarization in Python - The Easy Way (Beginner).srt - 7.81 KB
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1. Text Summarization Section Introduction.srt - 7.55 KB
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2. Text Summarization Using Vectors.srt - 7.3 KB
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10. Text Summarization Section Summary.srt - 4.41 KB
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3. Text Summarization Exercise Prompt.srt - 2.3 KB
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7. TextRank Exercise Prompt (Advanced).srt - 1.74 KB
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13. Latent Semantic Analysis (Latent Semantic Indexing)
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2. SVD (Singular Value Decomposition) Intuition.mp4 - 81.85 MB
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4. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 - 57.55 MB
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3. LSA LSI Applying SVD to NLP.mp4 - 34.42 MB
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5. LSA LSI Exercises.mp4 - 29.05 MB
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1. LSA LSI Section Introduction.mp4 - 20.95 MB
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2. SVD (Singular Value Decomposition) Intuition.srt - 15.4 KB
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3. LSA LSI Applying SVD to NLP.srt - 10.25 KB
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4. Latent Semantic Analysis Latent Semantic Indexing in Python.srt - 10.09 KB
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5. LSA LSI Exercises.srt - 7.34 KB
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1. LSA LSI Section Introduction.srt - 5.21 KB
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[CourseClub.Me].url - 122 B
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[GigaCourse.Com].url - 49 B
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15. The Neuron
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4. Text Classification in Tensorflow.mp4 - 81.66 MB
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2. Fitting a Line.mp4 - 68.61 MB
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6. How does a model learn.mp4 - 51.59 MB
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5. The Neuron.mp4 - 45.25 MB
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3. Classification Code Preparation.mp4 - 32.88 MB
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1. The Neuron - Section Introduction.mp4 - 11.01 MB
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7. The Neuron - Section Summary.mp4 - 10.32 MB
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2. Fitting a Line.srt - 18.38 KB
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6. How does a model learn.srt - 14.36 KB
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5. The Neuron.srt - 12.66 KB
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4. Text Classification in Tensorflow.srt - 11.71 KB
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3. Classification Code Preparation.srt - 9.52 KB
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1. The Neuron - Section Introduction.srt - 2.94 KB
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7. The Neuron - Section Summary.srt - 2.19 KB
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1. Introduction
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1. Introduction and Outline.mp4 - 72.97 MB
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2. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 - 26.66 MB
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1. Introduction and Outline.srt - 15.47 KB
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2. Are You Beginner, Intermediate, or Advanced All are OK!.srt - 7.22 KB
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12. Topic Modeling
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6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 - 72.39 MB
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5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 - 60.18 MB
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2. Latent Dirichlet Allocation (LDA) - Essentials.mp4 - 55.18 MB
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7. Non-Negative Matrix Factorization (NMF) Intuition.mp4 - 52.48 MB
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8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 - 36.04 MB
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1. Topic Modeling Section Introduction.mp4 - 17.04 MB
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3. LDA - Code Preparation.mp4 - 14.52 MB
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9. Topic Modeling Section Summary.mp4 - 9.81 MB
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4. LDA - Maybe Useful Picture (Optional).mp4 - 8.99 MB
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5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).srt - 20.17 KB
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2. Latent Dirichlet Allocation (LDA) - Essentials.srt - 15.16 KB
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7. Non-Negative Matrix Factorization (NMF) Intuition.srt - 13.8 KB
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6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.srt - 13.27 KB
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3. LDA - Code Preparation.srt - 4.91 KB
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8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.srt - 4.88 KB
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1. Topic Modeling Section Introduction.srt - 4.09 KB
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4. LDA - Maybe Useful Picture (Optional).srt - 2.52 KB
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9. Topic Modeling Section Summary.srt - 1.99 KB
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5. Markov Models (Intermediate)
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8. Building a Text Classifier (Code pt 2).mp4 - 72.22 MB
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11. Language Model (Code pt 1).mp4 - 62.83 MB
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7. Building a Text Classifier (Code pt 1).mp4 - 57.68 MB
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12. Language Model (Code pt 2).mp4 - 52.43 MB
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3. The Markov Model.mp4 - 45.84 MB
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9. Language Model (Theory).mp4 - 44.97 MB
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4. Probability Smoothing and Log-Probabilities.mp4 - 34.06 MB
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2. The Markov Property.mp4 - 32.25 MB
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6. Building a Text Classifier (Exercise Prompt).mp4 - 29.36 MB
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5. Building a Text Classifier (Theory).mp4 - 28.93 MB
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10. Language Model (Exercise Prompt).mp4 - 28.8 MB
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13. Markov Models Section Summary.mp4 - 15.56 MB
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1. Markov Models Section Introduction.mp4 - 13.09 MB
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3. The Markov Model.srt - 16.5 KB
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8. Building a Text Classifier (Code pt 2).srt - 13.81 KB
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9. Language Model (Theory).srt - 13.29 KB
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11. Language Model (Code pt 1).srt - 13.16 KB
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7. Building a Text Classifier (Code pt 1).srt - 11.82 KB
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12. Language Model (Code pt 2).srt - 11.3 KB
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4. Probability Smoothing and Log-Probabilities.srt - 10.28 KB
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2. The Markov Property.srt - 9.45 KB
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5. Building a Text Classifier (Theory).srt - 9.45 KB
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10. Language Model (Exercise Prompt).srt - 8.99 KB
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6. Building a Text Classifier (Exercise Prompt).srt - 8.81 KB
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13. Markov Models Section Summary.srt - 3.96 KB
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1. Markov Models Section Introduction.srt - 3.46 KB
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[CourseClub.Me].url - 122 B
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[GigaCourse.Com].url - 49 B
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21. Extra Help With Python Coding for Beginners FAQ
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1. How to Code by Yourself (part 1).mp4 - 71.86 MB
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3. Proof that using Jupyter Notebook is the same as not using it.mp4 - 69.42 MB
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2. How to Code by Yourself (part 2).mp4 - 49.16 MB
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1. How to Code by Yourself (part 1).srt - 22.7 KB
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3. Proof that using Jupyter Notebook is the same as not using it.srt - 14.32 KB
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2. How to Code by Yourself (part 2).srt - 13.3 KB
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[CourseClub.Me].url - 122 B
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[GigaCourse.Com].url - 49 B
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2. Getting Set Up
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2. How to use Github & Extra Coding Tips (Optional).mp4 - 63.88 MB
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1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 - 43.56 MB
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3. Where to get the code, notebooks, and data.mp4 - 26.86 MB
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5. Temporary 403 Errors.mp4 - 22 MB
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4. How to Succeed in This Course.mp4 - 16.27 MB
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2. How to use Github & Extra Coding Tips (Optional).srt - 15.71 KB
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1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt - 11.99 KB
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3. Where to get the code, notebooks, and data.srt - 6.33 KB
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4. How to Succeed in This Course.srt - 4.44 KB
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5. Temporary 403 Errors.srt - 3.71 KB
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1.1 Data Links.html - 157 B
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3.2 Data Links.html - 157 B
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1.2 Github Link.html - 139 B
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3.3 Github Link.html - 139 B
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3.1 Code Link.html - 125 B
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10. Sentiment Analysis
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2. Logistic Regression Intuition (pt 1).mp4 - 63.58 MB
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6. Sentiment Analysis in Python (pt 1).mp4 - 63.16 MB
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7. Sentiment Analysis in Python (pt 2).mp4 - 51.97 MB
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1. Sentiment Analysis - Problem Description.mp4 - 42.71 MB
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4. Logistic Regression Training and Interpretation (pt 3).mp4 - 39.63 MB
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3. Multiclass Logistic Regression (pt 2).mp4 - 23.61 MB
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5. Sentiment Analysis - Exercise Prompt.mp4 - 16.56 MB
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2. Logistic Regression Intuition (pt 1).srt - 22.54 KB
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6. Sentiment Analysis in Python (pt 1).srt - 11.63 KB
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4. Logistic Regression Training and Interpretation (pt 3).srt - 10.83 KB
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1. Sentiment Analysis - Problem Description.srt - 9.84 KB
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7. Sentiment Analysis in Python (pt 2).srt - 9.74 KB
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3. Multiclass Logistic Regression (pt 2).srt - 8.46 KB
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5. Sentiment Analysis - Exercise Prompt.srt - 5.09 KB
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20. Setting Up Your Environment FAQ
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2. Anaconda Environment Setup.mp4 - 52.63 MB
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3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 - 50.9 MB
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1. Pre-Installation Check.mp4 - 22.76 MB
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2. Anaconda Environment Setup.srt - 20.13 KB
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3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt - 14.61 KB
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1. Pre-Installation Check.srt - 6.59 KB
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19. Course Conclusion
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2. Where is BERT, ChatGPT, GPT-4, ....mp4 - 42.82 MB
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1. What to Learn Next.mp4 - 37.39 MB
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2. Where is BERT, ChatGPT, GPT-4, ....srt - 10.64 KB
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1. What to Learn Next.srt - 9.07 KB
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23. Appendix FAQ Finale
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2. BONUS.mp4 - 40.46 MB
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1. What is the Appendix.mp4 - 16.4 MB
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2. BONUS.srt - 8.06 KB
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1. What is the Appendix.srt - 3.8 KB
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8. Machine Learning Models (Introduction)
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1. Machine Learning Models (Introduction).mp4 - 29.6 MB
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1. Machine Learning Models (Introduction).srt - 7.84 KB
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4. Probabilistic Models (Introduction)
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1. Probabilistic Models (Introduction).mp4 - 26.91 MB
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1. Probabilistic Models (Introduction).srt - 6.28 KB
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14. Deep Learning (Introduction)
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1. Deep Learning Introduction (Intermediate-Advanced).mp4 - 24.53 MB
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1. Deep Learning Introduction (Intermediate-Advanced).srt - 6.76 KB
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0. Websites you may like
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[CourseClub.Me].url - 122 B
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[GigaCourse.Com].url - 49 B
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[CourseClub.Me].url - 122 B
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[GigaCourse.Com].url - 49 B
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InfoHash:
7838A37F4013B7920299208AE9E6F98748E05B45
Last updated:
Apr 14, 2024
File count:
331 B
File Category:
1
Tags:
gigacourse, udemy, machine, learning, natural, language, processing, python