Udemy - Deep Learning Advanced Natural Language Processing and RNNs (4.2025)
File List
- 09. Setting Up Your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.mp4 319.4 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/7. CNN Code (part 1).mp4 172.2 MB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 136.4 MB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 134.8 MB
- 05. Attention/5. Attention Code 1.mp4 115.6 MB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 108.5 MB
- 09. Setting Up Your Environment (FAQ by Student Request)/3. How to How to install Numpy, Theano, Tensorflow, etc.mp4 100.2 MB
- 04. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4 96.8 MB
- 04. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4 96.3 MB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 93.5 MB
- 06. Memory Networks/3. Memory Networks Code 1.mp4 92.3 MB
- 05. Attention/8. Building a Chatbot without any more Code.mp4 78.1 MB
- 06. Memory Networks/4. Memory Networks Code 2.mp4 61.8 MB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 60.2 MB
- 04. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4 50.1 MB
- 07. Keras and Tensorflow 2 Basics/2. (Review) Keras Neural Network in Code.mp4 49.2 MB
- 05. Attention/6. Attention Code 2.mp4 47.2 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/5. What is a CNN.mp4 45.3 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/8. CNN Code (part 2).mp4 45.0 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/12. A Simple RNN Experiment.mp4 43.2 MB
- 06. Memory Networks/5. Memory Networks Code 3.mp4 42.1 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/3. What is a word embedding.mp4 41.3 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/15. Suggestion Box.mp4 39.8 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/9. What is an RNN.mp4 37.4 MB
- 03. Bidirectional RNNs/5. Image Classification Code.mp4 37.3 MB
- 03. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4 37.1 MB
- 04. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4 37.1 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/11. Different Types of RNN Tasks.mp4 36.4 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/13. RNN Code.mp4 35.4 MB
- 05. Attention/2. Attention Theory.mp4 34.4 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/10. GRUs and LSTMs.mp4 33.5 MB
- 03. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4 32.4 MB
- 12. Appendix FAQ Finale/2. BONUS.mp4 31.0 MB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4 29.3 MB
- 07. Keras and Tensorflow 2 Basics/3. (Review) Keras Functional API.mp4 29.1 MB
- 06. Memory Networks/1. Memory Networks Section Introduction.mp4 25.8 MB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 23.7 MB
- 05. Attention/4. Helpful Implementation Details.mp4 23.0 MB
- 03. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4 21.0 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/6. Where to get the data.mp4 20.3 MB
- 04. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4 19.9 MB
- 04. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4 17.6 MB
- 06. Memory Networks/2. Memory Networks Theory.mp4 17.0 MB
- 03. Bidirectional RNNs/3. Bidirectional RNN Code.mp4 15.3 MB
- 07. Keras and Tensorflow 2 Basics/1. (Review) Keras Discussion.mp4 15.3 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/1. Review Section Introduction.mp4 13.5 MB
- 08. Course Conclusion/1. What to Learn Next.mp4 13.4 MB
- 09. Setting Up Your Environment (FAQ by Student Request)/1. Pre-Installation Check.mp4 13.0 MB
- 01. Welcome/3. Where to get the code.mp4 11.1 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/4. Using word embeddings.mp4 10.9 MB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4 10.4 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/14. Review Section Summary.mp4 10.3 MB
- 01. Welcome/4. How to Succeed in this Course.mp4 9.0 MB
- 12. Appendix FAQ Finale/1. What is the Appendix.mp4 8.9 MB
- 04. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.mp4 8.9 MB
- 06. Memory Networks/6. Memory Networks Section Summary.mp4 8.9 MB
- 05. Attention/9. Attention Section Summary.mp4 8.9 MB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/2. How to Open Files for Windows Users.mp4 8.5 MB
- 04. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.mp4 7.7 MB
- 03. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.mp4 7.3 MB
- 05. Attention/7. Visualizing Attention.mp4 7.2 MB
- 04. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.mp4 7.0 MB
- 07. Keras and Tensorflow 2 Basics/4. (Review) How to easily convert Keras into Tensorflow 2.0 code.mp4 6.2 MB
- 01. Welcome/2. Outline.mp4 4.7 MB
- 05. Attention/1. Attention Section Introduction.mp4 4.7 MB
- 05. Attention/3. Teacher Forcing.mp4 4.1 MB
- 01. Welcome/1. Introduction.mp4 3.8 MB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 33.0 KB
- 05. Attention/2. Attention Theory.vtt 24.7 KB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 24.3 KB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).vtt 23.0 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/7. CNN Code (part 1).vtt 21.0 KB
- 09. Setting Up Your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.vtt 20.1 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/3. What is a word embedding.vtt 20.0 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/5. What is a CNN.vtt 18.2 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/9. What is an RNN.vtt 17.7 KB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 17.6 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/11. Different Types of RNN Tasks.vtt 15.9 KB
- 05. Attention/4. Helpful Implementation Details.vtt 15.7 KB
- 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).vtt 15.3 KB
- 09. Setting Up Your Environment (FAQ by Student Request)/3. How to How to install Numpy, Theano, Tensorflow, etc.vtt 14.8 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/10. GRUs and LSTMs.vtt 14.3 KB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).vtt 14.1 KB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.vtt 14.1 KB
- 06. Memory Networks/1. Memory Networks Section Introduction.vtt 13.4 KB
- 06. Memory Networks/2. Memory Networks Theory.vtt 13.0 KB
- 05. Attention/5. Attention Code 1.vtt 12.0 KB
- 05. Attention/8. Building a Chatbot without any more Code.vtt 12.0 KB
- 03. Bidirectional RNNs/1. Bidirectional RNNs Motivation.vtt 11.2 KB
- 04. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.vtt 11.1 KB
- 06. Memory Networks/3. Memory Networks Code 1.vtt 10.1 KB
- 07. Keras and Tensorflow 2 Basics/1. (Review) Keras Discussion.vtt 9.9 KB
- 04. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.vtt 9.9 KB
- 04. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.vtt 9.6 KB
- 04. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.vtt 9.0 KB
- 04. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.vtt 8.9 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/8. CNN Code (part 2).vtt 8.2 KB
- 03. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.vtt 8.0 KB
- 07. Keras and Tensorflow 2 Basics/2. (Review) Keras Neural Network in Code.vtt 7.8 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/12. A Simple RNN Experiment.vtt 7.7 KB
- 06. Memory Networks/5. Memory Networks Code 3.vtt 7.3 KB
- 03. Bidirectional RNNs/5. Image Classification Code.vtt 7.1 KB
- 12. Appendix FAQ Finale/2. BONUS.vtt 7.1 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/6. Where to get the data.vtt 6.8 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/14. Review Section Summary.vtt 6.8 KB
- 01. Welcome/3. Where to get the code.vtt 6.7 KB
- 09. Setting Up Your Environment (FAQ by Student Request)/1. Pre-Installation Check.vtt 6.4 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/4. Using word embeddings.vtt 6.4 KB
- 04. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.vtt 6.3 KB
- 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.vtt 6.2 KB
- 06. Memory Networks/4. Memory Networks Code 2.vtt 6.2 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/1. Review Section Introduction.vtt 6.2 KB
- 03. Bidirectional RNNs/2. Bidirectional RNN Experiment.vtt 6.2 KB
- 01. Welcome/2. Outline.vtt 6.1 KB
- 07. Keras and Tensorflow 2 Basics/3. (Review) Keras Functional API.vtt 5.3 KB
- 06. Memory Networks/6. Memory Networks Section Summary.vtt 5.2 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/15. Suggestion Box.vtt 4.8 KB
- 01. Welcome/4. How to Succeed in this Course.vtt 4.6 KB
- 05. Attention/9. Attention Section Summary.vtt 4.6 KB
- 04. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.vtt 4.6 KB
- 05. Attention/6. Attention Code 2.vtt 4.4 KB
- 04. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.vtt 4.3 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/13. RNN Code.vtt 4.3 KB
- 12. Appendix FAQ Finale/1. What is the Appendix.vtt 4.0 KB
- 01. Welcome/1. Introduction.vtt 3.9 KB
- 04. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.vtt 3.9 KB
- 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/2. How to Open Files for Windows Users.vtt 3.4 KB
- 03. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.vtt 3.2 KB
- 05. Attention/1. Attention Section Introduction.vtt 3.2 KB
- 05. Attention/7. Visualizing Attention.vtt 3.2 KB
- 03. Bidirectional RNNs/3. Bidirectional RNN Code.vtt 2.9 KB
- 05. Attention/3. Teacher Forcing.vtt 2.7 KB
- 07. Keras and Tensorflow 2 Basics/4. (Review) How to easily convert Keras into Tensorflow 2.0 code.vtt 2.2 KB
- 01. Welcome/3. Github-Link.txt 59 bytes
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