[FreeTutorials.Eu] Udemy - Deep Learning Advanced NLP and RNNs

Creation Time	Feb. 24, 2025, 8:03 p.m.
Last Access Time	April 3, 2026, 2:49 p.m.
File Size	3.0 GB
Keywords	and NLP RNNs FreeTutorials - Deep Udemy Learning Eu Advanced
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Total Files	127
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8. Appendix/2. Windows-Focused Environment Setup 2018.mp4 193.3 MB
8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4 166.4 MB
2. Review/6. CNN Code (part 1).mp4 148.6 MB
8. Appendix/10. What order should I take your courses in (part 2).mp4 122.7 MB
8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 115.8 MB
5. Attention/5. Attention Code 1.mp4 99.9 MB
8. Appendix/9. What order should I take your courses in (part 1).mp4 88.0 MB
4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4 84.3 MB
4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4 82.6 MB
8. Appendix/6. How to Code by Yourself (part 1).mp4 82.1 MB
6. Memory Networks/3. Memory Networks Code 1.mp4 79.6 MB
8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
5. Attention/8. Building a Chatbot without any more Code.mp4 76.2 MB
4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4 66.6 MB
7. Basics Review/2. (Review) Keras Neural Network in Code.mp4 66.1 MB
2. Review/4. What is a CNN.mp4 62.0 MB
5. Attention/2. Attention Theory.mp4 61.8 MB
2. Review/7. CNN Code (part 2).mp4 59.3 MB
2. Review/2. What is a word embedding.mp4 57.5 MB
2. Review/10. Different Types of RNN Tasks.mp4 56.8 MB
2. Review/8. What is an RNN.mp4 56.6 MB
8. Appendix/7. How to Code by Yourself (part 2).mp4 56.2 MB
2. Review/11. A Simple RNN Experiment.mp4 56.0 MB
6. Memory Networks/5. Memory Networks Code 3.mp4 55.8 MB
6. Memory Networks/4. Memory Networks Code 2.mp4 53.6 MB
4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4 50.6 MB
2. Review/9. GRUs and LSTMs.mp4 49.6 MB
3. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4 48.7 MB
3. Bidirectional RNNs/5. Image Classification Code.mp4 48.6 MB
5. Attention/6. Attention Code 2.mp4 41.6 MB
5. Attention/4. Helpful Implementation Details.mp4 40.9 MB
6. Memory Networks/1. Memory Networks Section Introduction.mp4 39.2 MB
8. Appendix/5. How to Succeed in this Course (Long Version).mp4 39.0 MB
7. Basics Review/3. (Review) Keras Functional API.mp4 38.6 MB
3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4 33.3 MB
3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4 32.8 MB
4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4 32.5 MB
4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4 31.1 MB
2. Review/12. RNN Code.mp4 31.1 MB
6. Memory Networks/2. Memory Networks Theory.mp4 30.4 MB
7. Basics Review/1. (Review) Keras Discussion.mp4 27.6 MB
2. Review/5. Where to get the data.mp4 27.1 MB
3. Bidirectional RNNs/3. Bidirectional RNN Code.mp4 22.7 MB
2. Review/1. Review Section Introduction.mp4 20.8 MB
2. Review/13. Review Section Summary.mp4 19.6 MB
1. Welcome/3. Where to get the code.mp4 19.6 MB
8. Appendix/11. Python 2 vs Python 3.mp4 18.8 MB
2. Review/3. Using word embeddings.mp4 18.7 MB
8. Appendix/1. What is the Appendix.mp4 17.7 MB
1. Welcome/4. How to Succeed in this Course.mp4 17.4 MB
1. Welcome/2. Outline.mp4 16.1 MB
4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.mp4 16.1 MB
6. Memory Networks/6. Memory Networks Section Summary.mp4 16.1 MB
1. Welcome/1. Introduction.mp4 14.4 MB
3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.mp4 14.0 MB
5. Attention/9. Attention Section Summary.mp4 13.9 MB
4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.mp4 13.6 MB
8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.mp4 13.1 MB
4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.mp4 12.5 MB
5. Attention/7. Visualizing Attention.mp4 10.4 MB
5. Attention/1. Attention Section Introduction.mp4 8.4 MB
5. Attention/3. Teacher Forcing.mp4 7.2 MB
8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.0 KB
5. Attention/2. Attention Theory.vtt 20.9 KB
8. Appendix/10. What order should I take your courses in (part 2).vtt 20.3 KB
8. Appendix/6. How to Code by Yourself (part 1).vtt 19.6 KB
2. Review/6. CNN Code (part 1).vtt 17.5 KB
8. Appendix/2. Windows-Focused Environment Setup 2018.vtt 17.4 KB
2. Review/2. What is a word embedding.vtt 16.7 KB
2. Review/4. What is a CNN.vtt 15.7 KB
2. Review/8. What is an RNN.vtt 15.1 KB
8. Appendix/9. What order should I take your courses in (part 1).vtt 14.2 KB
2. Review/10. Different Types of RNN Tasks.vtt 13.5 KB
5. Attention/4. Helpful Implementation Details.vtt 13.1 KB
8. Appendix/5. How to Succeed in this Course (Long Version).vtt 12.8 KB
8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....vtt 12.4 KB
8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 12.2 KB
2. Review/9. GRUs and LSTMs.vtt 12.1 KB
8. Appendix/7. How to Code by Yourself (part 2).vtt 11.6 KB
6. Memory Networks/1. Memory Networks Section Introduction.vtt 11.1 KB
6. Memory Networks/2. Memory Networks Theory.vtt 10.7 KB
5. Attention/5. Attention Code 1.vtt 10.3 KB
5. Attention/8. Building a Chatbot without any more Code.vtt 10.1 KB
4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.vtt 9.5 KB
3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.vtt 9.2 KB
6. Memory Networks/3. Memory Networks Code 1.vtt 8.4 KB
4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.vtt 8.3 KB
4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.vtt 8.1 KB
7. Basics Review/1. (Review) Keras Discussion.vtt 8.0 KB
4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.vtt 7.6 KB
4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.vtt 7.5 KB
2. Review/7. CNN Code (part 2).vtt 6.9 KB
3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.vtt 6.8 KB
2. Review/11. A Simple RNN Experiment.vtt 6.7 KB
7. Basics Review/2. (Review) Keras Neural Network in Code.vtt 6.5 KB
6. Memory Networks/5. Memory Networks Code 3.vtt 6.2 KB
3. Bidirectional RNNs/5. Image Classification Code.vtt 5.8 KB
1. Welcome/3. Where to get the code.vtt 5.7 KB
2. Review/5. Where to get the data.vtt 5.7 KB
2. Review/13. Review Section Summary.vtt 5.6 KB
4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.vtt 5.4 KB
2. Review/3. Using word embeddings.vtt 5.4 KB
8. Appendix/11. Python 2 vs Python 3.vtt 5.3 KB
2. Review/1. Review Section Introduction.vtt 5.3 KB
1. Welcome/2. Outline.vtt 5.2 KB
6. Memory Networks/4. Memory Networks Code 2.vtt 5.2 KB
3. Bidirectional RNNs/2. Bidirectional RNN Experiment.vtt 5.2 KB
7. Basics Review/3. (Review) Keras Functional API.vtt 4.7 KB
6. Memory Networks/6. Memory Networks Section Summary.vtt 4.4 KB
5. Attention/9. Attention Section Summary.vtt 3.9 KB
4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.vtt 3.8 KB
4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.vtt 3.7 KB
2. Review/12. RNN Code.vtt 3.7 KB
5. Attention/6. Attention Code 2.vtt 3.7 KB
1. Welcome/4. How to Succeed in this Course.vtt 3.5 KB
1. Welcome/1. Introduction.vtt 3.3 KB
4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.vtt 3.3 KB
8. Appendix/1. What is the Appendix.vtt 3.3 KB
8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.vtt 3.0 KB
5. Attention/7. Visualizing Attention.vtt 2.7 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 2.4 KB
5. Attention/3. Teacher Forcing.vtt 2.3 KB
[FTU Forum].url 1.3 KB
[FreeCoursesOnline.Me].url 133 bytes
[FreeTutorials.Eu].url 129 bytes

[FreeTutorials.Eu] Udemy - Deep Learning Advanced NLP and RNNs

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