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[FreeTutorials.Eu] Udemy - Deep Learning Advanced NLP and RNNs
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[FreeTutorials.Eu] Udemy - Deep Learning Advanced NLP and RNNs
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2021-03-16
最近下载:
2024-11-29
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文件列表
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
[FTU Forum].url
1.4 kB
[FreeCoursesOnline.Me].url
133 Bytes
[FreeTutorials.Eu].url
129 Bytes
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