Udemy - Deep Learning Advanced Natural Language Processing and RNNs (4.2025)

磁力链接/BT种子名称

Udemy - Deep Learning Advanced Natural Language Processing and RNNs (4.2025)

磁力链接/BT种子简介

种子哈希：438b3fd1f3c5473bde89359c5f0be535932bf5d4
文件大小： 2.8G
已经下载：72次
下载速度：极快
收录时间：2025-07-30
最近下载：2025-09-30

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磁力链接下载

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文件列表

  • 09. Setting Up Your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.mp4 334.9 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/7. CNN Code (part 1).mp4 180.5 MB
  • 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 143.0 MB
  • 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 141.4 MB
  • 05. Attention/5. Attention Code 1.mp4 121.2 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 113.8 MB
  • 09. Setting Up Your Environment (FAQ by Student Request)/3. How to How to install Numpy, Theano, Tensorflow, etc.mp4 105.1 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4 101.5 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4 101.0 MB
  • 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 98.1 MB
  • 06. Memory Networks/3. Memory Networks Code 1.mp4 96.8 MB
  • 05. Attention/8. Building a Chatbot without any more Code.mp4 81.8 MB
  • 06. Memory Networks/4. Memory Networks Code 2.mp4 64.8 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 63.1 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4 52.5 MB
  • 07. Keras and Tensorflow 2 Basics/2. (Review) Keras Neural Network in Code.mp4 51.6 MB
  • 05. Attention/6. Attention Code 2.mp4 49.5 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/5. What is a CNN.mp4 47.4 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/8. CNN Code (part 2).mp4 47.2 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/12. A Simple RNN Experiment.mp4 45.3 MB
  • 06. Memory Networks/5. Memory Networks Code 3.mp4 44.2 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/3. What is a word embedding.mp4 43.3 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/15. Suggestion Box.mp4 41.8 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/9. What is an RNN.mp4 39.2 MB
  • 03. Bidirectional RNNs/5. Image Classification Code.mp4 39.1 MB
  • 03. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4 38.9 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4 38.9 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/11. Different Types of RNN Tasks.mp4 38.2 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/13. RNN Code.mp4 37.1 MB
  • 05. Attention/2. Attention Theory.mp4 36.1 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/10. GRUs and LSTMs.mp4 35.1 MB
  • 03. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4 34.0 MB
  • 12. Appendix FAQ Finale/2. BONUS.mp4 32.5 MB
  • 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4 30.7 MB
  • 07. Keras and Tensorflow 2 Basics/3. (Review) Keras Functional API.mp4 30.6 MB
  • 06. Memory Networks/1. Memory Networks Section Introduction.mp4 27.0 MB
  • 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 24.8 MB
  • 05. Attention/4. Helpful Implementation Details.mp4 24.1 MB
  • 03. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4 22.0 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/6. Where to get the data.mp4 21.3 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4 20.9 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4 18.4 MB
  • 06. Memory Networks/2. Memory Networks Theory.mp4 17.8 MB
  • 03. Bidirectional RNNs/3. Bidirectional RNN Code.mp4 16.0 MB
  • 07. Keras and Tensorflow 2 Basics/1. (Review) Keras Discussion.mp4 16.0 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/1. Review Section Introduction.mp4 14.2 MB
  • 08. Course Conclusion/1. What to Learn Next.mp4 14.1 MB
  • 09. Setting Up Your Environment (FAQ by Student Request)/1. Pre-Installation Check.mp4 13.7 MB
  • 01. Welcome/3. Where to get the code.mp4 11.7 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/4. Using word embeddings.mp4 11.5 MB
  • 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4 10.9 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/14. Review Section Summary.mp4 10.8 MB
  • 01. Welcome/4. How to Succeed in this Course.mp4 9.4 MB
  • 12. Appendix FAQ Finale/1. What is the Appendix.mp4 9.3 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.mp4 9.3 MB
  • 06. Memory Networks/6. Memory Networks Section Summary.mp4 9.3 MB
  • 05. Attention/9. Attention Section Summary.mp4 9.3 MB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/2. How to Open Files for Windows Users.mp4 8.9 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.mp4 8.1 MB
  • 03. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.mp4 7.7 MB
  • 05. Attention/7. Visualizing Attention.mp4 7.6 MB
  • 04. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.mp4 7.4 MB
  • 07. Keras and Tensorflow 2 Basics/4. (Review) How to easily convert Keras into Tensorflow 2.0 code.mp4 6.5 MB
  • 01. Welcome/2. Outline.mp4 4.9 MB
  • 05. Attention/1. Attention Section Introduction.mp4 4.9 MB
  • 05. Attention/3. Teacher Forcing.mp4 4.3 MB
  • 01. Welcome/1. Introduction.mp4 4.0 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 33.8 kB
  • 05. Attention/2. Attention Theory.vtt 25.3 kB
  • 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 24.9 kB
  • 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).vtt 23.6 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/7. CNN Code (part 1).vtt 21.5 kB
  • 09. Setting Up Your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.vtt 20.6 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/3. What is a word embedding.vtt 20.5 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/5. What is a CNN.vtt 18.7 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/9. What is an RNN.vtt 18.1 kB
  • 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 18.0 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/11. Different Types of RNN Tasks.vtt 16.3 kB
  • 05. Attention/4. Helpful Implementation Details.vtt 16.1 kB
  • 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).vtt 15.7 kB
  • 09. Setting Up Your Environment (FAQ by Student Request)/3. How to How to install Numpy, Theano, Tensorflow, etc.vtt 15.1 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/10. GRUs and LSTMs.vtt 14.6 kB
  • 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).vtt 14.5 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 14.5 kB
  • 06. Memory Networks/1. Memory Networks Section Introduction.vtt 13.8 kB
  • 06. Memory Networks/2. Memory Networks Theory.vtt 13.3 kB
  • 05. Attention/5. Attention Code 1.vtt 12.3 kB
  • 05. Attention/8. Building a Chatbot without any more Code.vtt 12.3 kB
  • 03. Bidirectional RNNs/1. Bidirectional RNNs Motivation.vtt 11.5 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.vtt 11.4 kB
  • 06. Memory Networks/3. Memory Networks Code 1.vtt 10.3 kB
  • 07. Keras and Tensorflow 2 Basics/1. (Review) Keras Discussion.vtt 10.2 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.vtt 10.1 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.vtt 9.8 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.vtt 9.2 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.vtt 9.1 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/8. CNN Code (part 2).vtt 8.4 kB
  • 03. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.vtt 8.2 kB
  • 07. Keras and Tensorflow 2 Basics/2. (Review) Keras Neural Network in Code.vtt 8.0 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/12. A Simple RNN Experiment.vtt 7.9 kB
  • 06. Memory Networks/5. Memory Networks Code 3.vtt 7.4 kB
  • 03. Bidirectional RNNs/5. Image Classification Code.vtt 7.3 kB
  • 12. Appendix FAQ Finale/2. BONUS.vtt 7.2 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/6. Where to get the data.vtt 7.0 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/14. Review Section Summary.vtt 6.9 kB
  • 01. Welcome/3. Where to get the code.vtt 6.9 kB
  • 09. Setting Up Your Environment (FAQ by Student Request)/1. Pre-Installation Check.vtt 6.6 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/4. Using word embeddings.vtt 6.6 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.vtt 6.5 kB
  • 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.vtt 6.4 kB
  • 06. Memory Networks/4. Memory Networks Code 2.vtt 6.3 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/1. Review Section Introduction.vtt 6.3 kB
  • 03. Bidirectional RNNs/2. Bidirectional RNN Experiment.vtt 6.3 kB
  • 01. Welcome/2. Outline.vtt 6.3 kB
  • 07. Keras and Tensorflow 2 Basics/3. (Review) Keras Functional API.vtt 5.5 kB
  • 06. Memory Networks/6. Memory Networks Section Summary.vtt 5.3 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/15. Suggestion Box.vtt 4.9 kB
  • 01. Welcome/4. How to Succeed in this Course.vtt 4.7 kB
  • 05. Attention/9. Attention Section Summary.vtt 4.7 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.vtt 4.7 kB
  • 05. Attention/6. Attention Code 2.vtt 4.5 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.vtt 4.4 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/13. RNN Code.vtt 4.4 kB
  • 12. Appendix FAQ Finale/1. What is the Appendix.vtt 4.1 kB
  • 01. Welcome/1. Introduction.vtt 4.0 kB
  • 04. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.vtt 4.0 kB
  • 02. Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings/2. How to Open Files for Windows Users.vtt 3.5 kB
  • 03. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.vtt 3.3 kB
  • 05. Attention/1. Attention Section Introduction.vtt 3.3 kB
  • 05. Attention/7. Visualizing Attention.vtt 3.3 kB
  • 03. Bidirectional RNNs/3. Bidirectional RNN Code.vtt 2.9 kB
  • 05. Attention/3. Teacher Forcing.vtt 2.8 kB
  • 07. Keras and Tensorflow 2 Basics/4. (Review) How to easily convert Keras into Tensorflow 2.0 code.vtt 2.3 kB
  • 01. Welcome/3. Github-Link.txt 59 Bytes

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