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[FreeCourseLab.com] Udemy - Deep Learning Advanced NLP and RNNs

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  2. File Size：3.08 GB
  3. Creat Time：2024-09-21
  4. Active Degree：3
  5. Last Active：2024-10-03
  6. File Tags：FreeCourseLab  com  Udemy  Deep  Learning  Advanced  NLP  and  RNNs  
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File List:

    [FreeCourseLab.com] Udemy - Deep Learning Advanced NLP and RNNs

  1. 8. Appendix/2. Windows-Focused Environment Setup 2018.mp4 197.90 MB
  2. 8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4 170.44 MB
  3. 2. Review/6. CNN Code (part 1).mp4 152.18 MB
  4. 8. Appendix/10. What order should I take your courses in (part 2).mp4 125.59 MB
  5. 8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 118.63 MB
  6. 5. Attention/5. Attention Code 1.mp4 102.34 MB
  7. 8. Appendix/9. What order should I take your courses in (part 1).mp4 90.15 MB
  8. 4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4 86.37 MB
  9. 4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4 84.57 MB
  10. 8. Appendix/6. How to Code by Yourself (part 1).mp4 84.08 MB
  11. 6. Memory Networks/3. Memory Networks Code 1.mp4 81.53 MB
  12. 8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 80.14 MB
  13. 5. Attention/8. Building a Chatbot without any more Code.mp4 77.98 MB
  14. 4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4 68.16 MB
  15. 7. Basics Review/2. (Review) Keras Neural Network in Code.mp4 67.70 MB
  16. 2. Review/4. What is a CNN.mp4 63.46 MB
  17. 5. Attention/2. Attention Theory.mp4 63.30 MB
  18. 2. Review/7. CNN Code (part 2).mp4 60.71 MB
  19. 2. Review/2. What is a word embedding.mp4 58.91 MB
  20. 2. Review/10. Different Types of RNN Tasks.mp4 58.15 MB
  21. 2. Review/8. What is an RNN.mp4 57.97 MB
  22. 8. Appendix/7. How to Code by Yourself (part 2).mp4 57.57 MB
  23. 2. Review/11. A Simple RNN Experiment.mp4 57.34 MB
  24. 6. Memory Networks/5. Memory Networks Code 3.mp4 57.19 MB
  25. 6. Memory Networks/4. Memory Networks Code 2.mp4 54.83 MB
  26. 4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4 51.80 MB
  27. 2. Review/9. GRUs and LSTMs.mp4 50.83 MB
  28. 3. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4 49.87 MB
  29. 3. Bidirectional RNNs/5. Image Classification Code.mp4 49.79 MB
  30. 5. Attention/6. Attention Code 2.mp4 42.60 MB
  31. 5. Attention/4. Helpful Implementation Details.mp4 41.86 MB
  32. 6. Memory Networks/1. Memory Networks Section Introduction.mp4 40.17 MB
  33. 8. Appendix/5. How to Succeed in this Course (Long Version).mp4 39.94 MB
  34. 7. Basics Review/3. (Review) Keras Functional API.mp4 39.52 MB
  35. 3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4 34.15 MB
  36. 3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4 33.57 MB
  37. 4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4 33.29 MB
  38. 4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4 31.87 MB
  39. 2. Review/12. RNN Code.mp4 31.84 MB
  40. 6. Memory Networks/2. Memory Networks Theory.mp4 31.13 MB
  41. 7. Basics Review/1. (Review) Keras Discussion.mp4 28.30 MB
  42. 2. Review/5. Where to get the data.mp4 27.80 MB
  43. 3. Bidirectional RNNs/3. Bidirectional RNN Code.mp4 23.26 MB
  44. 2. Review/1. Review Section Introduction.mp4 21.25 MB
  45. 2. Review/13. Review Section Summary.mp4 20.12 MB
  46. 1. Welcome/3. Where to get the code.mp4 20.04 MB
  47. 8. Appendix/11. Python 2 vs Python 3.mp4 19.24 MB
  48. 2. Review/3. Using word embeddings.mp4 19.12 MB
  49. 8. Appendix/1. What is the Appendix.mp4 18.11 MB
  50. 1. Welcome/4. How to Succeed in this Course.mp4 17.83 MB
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