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文档列表

8. Appendix/2. Windows-Focused Environment Setup 2018.mp4 202.6 MB
8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4 174.5 MB
2. Review/6. CNN Code (part 1).mp4 155.8 MB
8. Appendix/10. What order should I take your courses in (part 2).mp4 128.6 MB
8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 121.5 MB
5. Attention/5. Attention Code 1.mp4 104.8 MB
8. Appendix/9. What order should I take your courses in (part 1).mp4 92.3 MB
4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4 88.4 MB
4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4 86.6 MB
8. Appendix/6. How to Code by Yourself (part 1).mp4 86.1 MB
6. Memory Networks/3. Memory Networks Code 1.mp4 83.5 MB
8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
5. Attention/8. Building a Chatbot without any more Code.mp4 79.9 MB
4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4 69.8 MB
7. Basics Review/2. (Review) Keras Neural Network in Code.mp4 69.3 MB
2. Review/4. What is a CNN.mp4 65.0 MB
5. Attention/2. Attention Theory.mp4 64.8 MB
2. Review/7. CNN Code (part 2).mp4 62.2 MB
2. Review/2. What is a word embedding.mp4 60.3 MB
2. Review/10. Different Types of RNN Tasks.mp4 59.5 MB
2. Review/8. What is an RNN.mp4 59.4 MB
8. Appendix/7. How to Code by Yourself (part 2).mp4 59.0 MB
2. Review/11. A Simple RNN Experiment.mp4 58.7 MB
6. Memory Networks/5. Memory Networks Code 3.mp4 58.6 MB
6. Memory Networks/4. Memory Networks Code 2.mp4 56.2 MB
4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4 53.0 MB
2. Review/9. GRUs and LSTMs.mp4 52.0 MB
3. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4 51.1 MB
3. Bidirectional RNNs/5. Image Classification Code.mp4 51.0 MB
5. Attention/6. Attention Code 2.mp4 43.6 MB
5. Attention/4. Helpful Implementation Details.mp4 42.9 MB
6. Memory Networks/1. Memory Networks Section Introduction.mp4 41.1 MB
8. Appendix/5. How to Succeed in this Course (Long Version).mp4 40.9 MB
7. Basics Review/3. (Review) Keras Functional API.mp4 40.5 MB
3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4 35.0 MB
3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4 34.4 MB
4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4 34.1 MB
4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4 32.6 MB
2. Review/12. RNN Code.mp4 32.6 MB
6. Memory Networks/2. Memory Networks Theory.mp4 31.9 MB
7. Basics Review/1. (Review) Keras Discussion.mp4 29.0 MB
2. Review/5. Where to get the data.mp4 28.5 MB
3. Bidirectional RNNs/3. Bidirectional RNN Code.mp4 23.8 MB
2. Review/1. Review Section Introduction.mp4 21.8 MB
2. Review/13. Review Section Summary.mp4 20.6 MB
1. Welcome/3. Where to get the code.mp4 20.5 MB
8. Appendix/11. Python 2 vs Python 3.mp4 19.7 MB
2. Review/3. Using word embeddings.mp4 19.6 MB
8. Appendix/1. What is the Appendix.mp4 18.5 MB
1. Welcome/4. How to Succeed in this Course.mp4 18.3 MB
1. Welcome/2. Outline.mp4 16.9 MB
4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.mp4 16.9 MB
6. Memory Networks/6. Memory Networks Section Summary.mp4 16.9 MB
1. Welcome/1. Introduction.mp4 15.1 MB
3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.mp4 14.7 MB
5. Attention/9. Attention Section Summary.mp4 14.6 MB
4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.mp4 14.3 MB
8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.mp4 13.7 MB
4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.mp4 13.1 MB
5. Attention/7. Visualizing Attention.mp4 10.9 MB
5. Attention/1. Attention Section Introduction.mp4 8.8 MB
5. Attention/3. Teacher Forcing.mp4 7.5 MB
8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.6 kB
5. Attention/2. Attention Theory.vtt 21.4 kB
8. Appendix/10. What order should I take your courses in (part 2).vtt 20.8 kB
8. Appendix/6. How to Code by Yourself (part 1).vtt 20.1 kB
2. Review/6. CNN Code (part 1).vtt 17.9 kB
8. Appendix/2. Windows-Focused Environment Setup 2018.vtt 17.8 kB
2. Review/2. What is a word embedding.vtt 17.1 kB
2. Review/4. What is a CNN.vtt 16.1 kB
2. Review/8. What is an RNN.vtt 15.5 kB
8. Appendix/9. What order should I take your courses in (part 1).vtt 14.5 kB
2. Review/10. Different Types of RNN Tasks.vtt 13.8 kB
5. Attention/4. Helpful Implementation Details.vtt 13.4 kB
8. Appendix/5. How to Succeed in this Course (Long Version).vtt 13.1 kB
8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....vtt 12.7 kB
8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
2. Review/9. GRUs and LSTMs.vtt 12.4 kB
8. Appendix/7. How to Code by Yourself (part 2).vtt 11.9 kB
6. Memory Networks/1. Memory Networks Section Introduction.vtt 11.3 kB
6. Memory Networks/2. Memory Networks Theory.vtt 11.0 kB
5. Attention/5. Attention Code 1.vtt 10.5 kB
5. Attention/8. Building a Chatbot without any more Code.vtt 10.3 kB
4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.vtt 9.7 kB
3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.vtt 9.5 kB
6. Memory Networks/3. Memory Networks Code 1.vtt 8.6 kB
4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.vtt 8.5 kB
4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.vtt 8.3 kB
7. Basics Review/1. (Review) Keras Discussion.vtt 8.2 kB
4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.vtt 7.7 kB
4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.vtt 7.6 kB
2. Review/7. CNN Code (part 2).vtt 7.1 kB
3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.vtt 6.9 kB
2. Review/11. A Simple RNN Experiment.vtt 6.8 kB
7. Basics Review/2. (Review) Keras Neural Network in Code.vtt 6.6 kB
6. Memory Networks/5. Memory Networks Code 3.vtt 6.3 kB
3. Bidirectional RNNs/5. Image Classification Code.vtt 6.0 kB
1. Welcome/3. Where to get the code.vtt 5.9 kB
2. Review/5. Where to get the data.vtt 5.8 kB
2. Review/13. Review Section Summary.vtt 5.7 kB
4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.vtt 5.5 kB
2. Review/3. Using word embeddings.vtt 5.5 kB
8. Appendix/11. Python 2 vs Python 3.vtt 5.5 kB
2. Review/1. Review Section Introduction.vtt 5.4 kB
1. Welcome/2. Outline.vtt 5.3 kB
6. Memory Networks/4. Memory Networks Code 2.vtt 5.3 kB
3. Bidirectional RNNs/2. Bidirectional RNN Experiment.vtt 5.3 kB
7. Basics Review/3. (Review) Keras Functional API.vtt 4.8 kB
6. Memory Networks/6. Memory Networks Section Summary.vtt 4.5 kB
5. Attention/9. Attention Section Summary.vtt 4.0 kB
4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.vtt 3.9 kB
4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.vtt 3.8 kB
2. Review/12. RNN Code.vtt 3.8 kB
5. Attention/6. Attention Code 2.vtt 3.8 kB
1. Welcome/4. How to Succeed in this Course.vtt 3.6 kB
1. Welcome/1. Introduction.vtt 3.4 kB
4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.vtt 3.4 kB
8. Appendix/1. What is the Appendix.vtt 3.4 kB
8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.vtt 3.1 kB
5. Attention/7. Visualizing Attention.vtt 2.8 kB
3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.vtt 2.7 kB
5. Attention/1. Attention Section Introduction.vtt 2.7 kB
3. Bidirectional RNNs/3. Bidirectional RNN Code.vtt 2.5 kB
5. Attention/3. Teacher Forcing.vtt 2.3 kB
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