MuerBT磁力搜索 BT种子搜索利器 免费下载BT种子,超5000万条种子数据

[FreeAllCourse.Com] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks

磁力链接/BT种子名称

[FreeAllCourse.Com] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks

磁力链接/BT种子简介

种子哈希:8b335e526d48a890f2c17a9f0a9017bcc88c3b20
文件大小: 3.35G
已经下载:1861次
下载速度:极快
收录时间:2021-04-28
最近下载:2025-10-01

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:8B335E526D48A890F2C17A9F0A9017BCC88C3B20
推荐使用PIKPAK网盘下载资源,10TB超大空间,不限制资源,无限次数离线下载,视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 抖音Max TikTok成人版 PornHub 听泉鉴鲍 少女日记 草榴社区 哆哔涩漫 呦乐园 萝莉岛 悠悠禁区 悠悠禁区 拔萝卜 疯马秀

最近搜索

反差户外 宾馆鸡 玩游戏++妹妹 七月新流出 海安中学 主动坐 4427736 风骚荡妇夜夜 完结 性感空 李小 绿帽淫妻多 mio hiragi 爽翻天 夫人 服不服啊 丰满女人 红底 abp-583 酒店气质 无水 原档 人妻下海 推特反差 kusuriya dashing 网黄推特 rape 抄底 tp探花 超极品模特

文件列表

  • 1. Welcome to the course/6.2 DL Colab Changes.zip.zip 293.5 MB
  • 1. Welcome to the course/1. Updates on Udemy Reviews.mp4 64.1 MB
  • 6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.mp4 58.5 MB
  • 14. RNN Intuition/6. Practical intuition.mp4 55.4 MB
  • 26. Building an AutoEncoder/16. THANK YOU bonus video.mp4 54.8 MB
  • 6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.mp4 53.2 MB
  • 26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.mp4 52.0 MB
  • 10. Building a CNN/12. Building a CNN - Step 9.mp4 49.1 MB
  • 14. RNN Intuition/5. LSTMs.mp4 48.2 MB
  • 4. Building an ANN/6. Building an ANN - Step 2.mp4 48.1 MB
  • 23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp4 47.9 MB
  • 18. SOMs Intuition/8. Reading an Advanced SOM.mp4 45.3 MB
  • 23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp4 45.1 MB
  • 9. CNN Intuition/8. Step 4 - Full Connection.mp4 44.8 MB
  • 30. Classification Template/5. Logistic Regression Implementation - Step 5.mp4 44.6 MB
  • 11. Homework - What's that pet/2. Homework Solution.mp4 42.9 MB
  • 23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp4 42.4 MB
  • 9. CNN Intuition/6. Step 2 - Pooling.mp4 42.2 MB
  • 15. Building a RNN/15. Building a RNN - Step 13.mp4 41.8 MB
  • 26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.mp4 39.8 MB
  • 5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.mp4 39.5 MB
  • 14. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp4 39.1 MB
  • 15. Building a RNN/6. Building a RNN - Step 4.mp4 38.9 MB
  • 19. Building a SOM/4. Building a SOM - Step 3.mp4 37.8 MB
  • 20. Mega Case Study/3. Mega Case Study - Step 3.mp4 36.9 MB
  • 26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.mp4 35.5 MB
  • 26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.mp4 35.3 MB
  • 9. CNN Intuition/10. Softmax & Cross-Entropy.mp4 34.8 MB
  • 22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.mp4 33.4 MB
  • 26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.mp4 33.1 MB
  • 1. Welcome to the course/2. What is Deep Learning.mp4 32.8 MB
  • 9. CNN Intuition/4. Step 1 - Convolution Operation.mp4 32.5 MB
  • 23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp4 32.5 MB
  • 19. Building a SOM/2. Building a SOM - Step 1.mp4 32.2 MB
  • 4. Building an ANN/9. Building an ANN - Step 5.mp4 31.0 MB
  • 3. ANN Intuition/2. The Neuron.mp4 31.0 MB
  • 9. CNN Intuition/3. What are convolutional neural networks.mp4 30.9 MB
  • 15. Building a RNN/13. Building a RNN - Step 11.mp4 30.7 MB
  • 23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp4 30.6 MB
  • 28. Regression & Classification Intuition/5. Logistic Regression Intuition.mp4 30.6 MB
  • 14. RNN Intuition/4. The Vanishing Gradient Problem.mp4 30.4 MB
  • 29. Data Preprocessing Template/4. Data Preprocessing - Step 4.mp4 30.4 MB
  • 19. Building a SOM/5. Building a SOM - Step 4.mp4 30.1 MB
  • 26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.mp4 29.7 MB
  • 26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.mp4 29.2 MB
  • 10. Building a CNN/7. Building a CNN - Step 4.mp4 28.5 MB
  • 3. ANN Intuition/5. How do Neural Networks learn.mp4 27.8 MB
  • 15. Building a RNN/7. Building a RNN - Step 5.mp4 27.5 MB
  • 26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.mp4 27.3 MB
  • 18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp4 26.3 MB
  • 22. Boltzmann Machine Intuition/2. Boltzmann Machine.mp4 26.2 MB
  • 22. Boltzmann Machine Intuition/6. Contrastive Divergence.mp4 26.1 MB
  • 23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp4 25.6 MB
  • 4. Building an ANN/5. Building an ANN - Step 1.mp4 25.5 MB
  • 3. ANN Intuition/4. How do Neural Networks work.mp4 24.7 MB
  • 23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp4 24.0 MB
  • 29. Data Preprocessing Template/5. Data Preprocessing - Step 5.mp4 24.0 MB
  • 29. Data Preprocessing Template/6. Data Preprocessing - Step 6.mp4 23.9 MB
  • 20. Mega Case Study/4. Mega Case Study - Step 4.mp4 23.8 MB
  • 29. Data Preprocessing Template/3. Data Preprocessing - Step 3.mp4 22.8 MB
  • 15. Building a RNN/17. Building a RNN - Step 15.mp4 22.7 MB
  • 15. Building a RNN/16. Building a RNN - Step 14.mp4 22.6 MB
  • 25. AutoEncoders Intuition/2. Auto Encoders.mp4 22.6 MB
  • 18. SOMs Intuition/4. K-Means Clustering (Refresher).mp4 22.3 MB
  • 23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp4 22.2 MB
  • 23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp4 22.1 MB
  • 15. Building a RNN/9. Building a RNN - Step 7.mp4 21.9 MB
  • 23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp4 21.8 MB
  • 10. Building a CNN/13. Building a CNN - Step 10.mp4 21.5 MB
  • 1. Welcome to the course/4. Installing Python.mp4 21.4 MB
  • 26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.mp4 21.1 MB
  • 6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.mp4 20.8 MB
  • 19. Building a SOM/3. Building a SOM - Step 2.mp4 20.4 MB
  • 10. Building a CNN/4. Building a CNN - Step 1.mp4 20.1 MB
  • 23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp4 19.7 MB
  • 3. ANN Intuition/6. Gradient Descent.mp4 19.4 MB
  • 18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp4 19.4 MB
  • 22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.mp4 19.3 MB
  • 23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp4 19.1 MB
  • 4. Building an ANN/12. Building an ANN - Step 8.mp4 19.1 MB
  • 4. Building an ANN/14. Building an ANN - Step 10.mp4 18.3 MB
  • 4. Building an ANN/13. Building an ANN - Step 9.mp4 17.7 MB
  • 3. ANN Intuition/7. Stochastic Gradient Descent.mp4 17.6 MB
  • 23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp4 17.5 MB
  • 4. Building an ANN/3. Business Problem Description.mp4 17.2 MB
  • 18. SOMs Intuition/2. How do Self-Organizing Maps Work.mp4 16.7 MB
  • 15. Building a RNN/5. Building a RNN - Step 3.mp4 16.7 MB
  • 29. Data Preprocessing Template/2. Data Preprocessing - Step 2.mp4 16.6 MB
  • 22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).mp4 16.5 MB
  • 15. Building a RNN/4. Building a RNN - Step 2.mp4 16.4 MB
  • 18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp4 16.2 MB
  • 23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp4 16.0 MB
  • 3. ANN Intuition/3. The Activation Function.mp4 15.5 MB
  • 9. CNN Intuition/5. Step 1(b) - ReLU Layer.mp4 14.8 MB
  • 15. Building a RNN/3. Building a RNN - Step 1.mp4 14.4 MB
  • 15. Building a RNN/14. Building a RNN - Step 12.srt 14.1 MB
  • 15. Building a RNN/14. Building a RNN - Step 12.mp4 14.1 MB
  • 15. Building a RNN/10. Building a RNN - Step 8.mp4 14.1 MB
  • 29. Data Preprocessing Template/1. Data Preprocessing - Step 1.mp4 13.9 MB
  • 18. SOMs Intuition/7. Live SOM example.mp4 13.3 MB
  • 10. Building a CNN/10. Building a CNN - Step 7.mp4 13.2 MB
  • 18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp4 12.9 MB
  • 30. Classification Template/1. Logistic Regression Implementation - Step 1.mp4 12.8 MB
  • 26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.mp4 12.4 MB
  • 30. Classification Template/6. Classification Template.mp4 12.3 MB
  • 25. AutoEncoders Intuition/6. Sparse Autoencoders.mp4 12.1 MB
  • 15. Building a RNN/12. Building a RNN - Step 10.mp4 12.0 MB
  • 26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.mp4 11.8 MB
  • 25. AutoEncoders Intuition/4. Training an Auto Encoder.mp4 11.7 MB
  • 23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp4 11.7 MB
  • 3. ANN Intuition/8. Backpropagation.mp4 11.5 MB
  • 22. Boltzmann Machine Intuition/7. Deep Belief Networks.mp4 10.8 MB
  • 10. Building a CNN/8. Building a CNN - Step 5.mp4 10.4 MB
  • 10. Building a CNN/9. Building a CNN - Step 6.mp4 10.2 MB
  • 30. Classification Template/4. Logistic Regression Implementation - Step 4.mp4 10.1 MB
  • 20. Mega Case Study/2. Mega Case Study - Step 2.mp4 10.1 MB
  • 28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp4 9.9 MB
  • 4. Building an ANN/11. Building an ANN - Step 7.mp4 9.4 MB
  • 4. Building an ANN/7. Building an ANN - Step 3.mp4 8.8 MB
  • 15. Building a RNN/11. Building a RNN - Step 9.mp4 8.6 MB
  • 30. Classification Template/2. Logistic Regression Implementation - Step 2.mp4 8.5 MB
  • 29. Data Preprocessing Template/7. Data Preprocessing Template.mp4 8.5 MB
  • 9. CNN Intuition/9. Summary.mp4 8.3 MB
  • 10. Building a CNN/3. Introduction to CNNs.mp4 8.2 MB
  • 14. RNN Intuition/7. EXTRA LSTM Variations.mp4 7.7 MB
  • 4. Building an ANN/10. Building an ANN - Step 6.mp4 7.4 MB
  • 10. Building a CNN/11. Building a CNN - Step 8.mp4 7.1 MB
  • 15. Building a RNN/8. Building a RNN - Step 6.mp4 7.1 MB
  • 15. Building a RNN/1. How to get the dataset.mp4 6.8 MB
  • 1. Welcome to the course/5. How to get the dataset.mp4 6.8 MB
  • 10. Building a CNN/1. How to get the dataset.mp4 6.8 MB
  • 19. Building a SOM/1. How to get the dataset.mp4 6.8 MB
  • 26. Building an AutoEncoder/1. How to get the dataset.mp4 6.8 MB
  • 4. Building an ANN/2. How to get the dataset.mp4 6.8 MB
  • 23. Building a Boltzmann Machine/1. How to get the dataset.mp4 6.8 MB
  • 25. AutoEncoders Intuition/5. Overcomplete hidden layers.mp4 6.7 MB
  • 30. Classification Template/3. Logistic Regression Implementation - Step 3.mp4 6.2 MB
  • 4. Building an ANN/8. Building an ANN - Step 4.mp4 6.2 MB
  • 10. Building a CNN/5. Building a CNN - Step 2.mp4 6.1 MB
  • 28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp4 5.6 MB
  • 9. CNN Intuition/2. Plan of attack.mp4 5.2 MB
  • 22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.mp4 5.1 MB
  • 3. ANN Intuition/1. Plan of Attack.mp4 5.0 MB
  • 25. AutoEncoders Intuition/7. Denoising Autoencoders.mp4 5.0 MB
  • 18. SOMs Intuition/1. Plan of attack.mp4 4.7 MB
  • 25. AutoEncoders Intuition/8. Contractive Autoencoders.mp4 4.6 MB
  • 20. Mega Case Study/1. Mega Case Study - Step 1.mp4 4.5 MB
  • 14. RNN Intuition/2. Plan of attack.mp4 4.4 MB
  • 25. AutoEncoders Intuition/9. Stacked Autoencoders.mp4 3.8 MB
  • 18. SOMs Intuition/3. Why revisit K-Means.mp4 3.6 MB
  • 25. AutoEncoders Intuition/1. Plan of attack.mp4 3.5 MB
  • 9. CNN Intuition/7. Step 3 - Flattening.mp4 3.4 MB
  • 22. Boltzmann Machine Intuition/1. Plan of attack.mp4 3.4 MB
  • 25. AutoEncoders Intuition/10. Deep Autoencoders.mp4 3.0 MB
  • 10. Building a CNN/6. Building a CNN - Step 3.mp4 2.3 MB
  • 25. AutoEncoders Intuition/3. A Note on Biases.mp4 2.1 MB
  • 28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp4 1.9 MB
  • 23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.srt 43.5 kB
  • 26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.srt 42.1 kB
  • 6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.srt 41.1 kB
  • 10. Building a CNN/12. Building a CNN - Step 9.srt 40.6 kB
  • 14. RNN Intuition/5. LSTMs.srt 40.3 kB
  • 9. CNN Intuition/8. Step 4 - Full Connection.srt 39.5 kB
  • 22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.srt 38.7 kB
  • 6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.srt 37.5 kB
  • 23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.srt 36.8 kB
  • 4. Building an ANN/6. Building an ANN - Step 2.srt 36.8 kB
  • 3. ANN Intuition/2. The Neuron.srt 36.6 kB
  • 19. Building a SOM/4. Building a SOM - Step 3.srt 36.0 kB
  • 30. Classification Template/5. Logistic Regression Implementation - Step 5.srt 35.8 kB
  • 26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.srt 35.5 kB
  • 9. CNN Intuition/10. Softmax & Cross-Entropy.srt 35.4 kB
  • 23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.srt 35.0 kB
  • 28. Regression & Classification Intuition/5. Logistic Regression Intuition.srt 33.4 kB
  • 9. CNN Intuition/4. Step 1 - Convolution Operation.srt 33.0 kB
  • 14. RNN Intuition/3. The idea behind Recurrent Neural Networks.srt 32.5 kB
  • 26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.srt 31.9 kB
  • 9. CNN Intuition/3. What are convolutional neural networks.srt 31.8 kB
  • 22. Boltzmann Machine Intuition/6. Contrastive Divergence.srt 31.8 kB
  • 15. Building a RNN/15. Building a RNN - Step 13.srt 31.7 kB
  • 18. SOMs Intuition/4. K-Means Clustering (Refresher).srt 31.6 kB
  • 11. Homework - What's that pet/2. Homework Solution.srt 31.5 kB
  • 22. Boltzmann Machine Intuition/2. Boltzmann Machine.srt 31.0 kB
  • 14. RNN Intuition/4. The Vanishing Gradient Problem.srt 30.4 kB
  • 18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).srt 29.8 kB
  • 18. SOMs Intuition/8. Reading an Advanced SOM.srt 29.2 kB
  • 9. CNN Intuition/6. Step 2 - Pooling.srt 29.2 kB
  • 14. RNN Intuition/6. Practical intuition.srt 28.6 kB
  • 20. Mega Case Study/3. Mega Case Study - Step 3.srt 28.4 kB
  • 26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.srt 28.3 kB
  • 3. ANN Intuition/5. How do Neural Networks learn.srt 28.1 kB
  • 26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.srt 27.8 kB
  • 10. Building a CNN/7. Building a CNN - Step 4.srt 27.3 kB
  • 4. Building an ANN/5. Building an ANN - Step 1.srt 27.2 kB
  • 3. ANN Intuition/4. How do Neural Networks work.srt 26.9 kB
  • 19. Building a SOM/2. Building a SOM - Step 1.srt 26.9 kB
  • 15. Building a RNN/6. Building a RNN - Step 4.srt 26.0 kB
  • 18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).srt 25.6 kB
  • 4. Building an ANN/9. Building an ANN - Step 5.srt 25.5 kB
  • 23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.srt 25.3 kB
  • 23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.srt 25.2 kB
  • 29. Data Preprocessing Template/4. Data Preprocessing - Step 4.srt 24.6 kB
  • 26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.srt 24.6 kB
  • 26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.srt 24.5 kB
  • 1. Welcome to the course/2. What is Deep Learning.srt 24.4 kB
  • 26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.srt 23.6 kB
  • 23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.srt 23.1 kB
  • 22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).srt 22.4 kB
  • 25. AutoEncoders Intuition/2. Auto Encoders.srt 21.9 kB
  • 19. Building a SOM/5. Building a SOM - Step 4.srt 21.9 kB
  • 20. Mega Case Study/4. Mega Case Study - Step 4.srt 21.9 kB
  • 29. Data Preprocessing Template/6. Data Preprocessing - Step 6.srt 21.9 kB
  • 29. Data Preprocessing Template/5. Data Preprocessing - Step 5.srt 21.7 kB
  • 5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.srt 21.7 kB
  • 23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.srt 21.3 kB
  • 23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.srt 21.0 kB
  • 15. Building a RNN/7. Building a RNN - Step 5.srt 20.1 kB
  • 29. Data Preprocessing Template/3. Data Preprocessing - Step 3.srt 19.9 kB
  • 19. Building a SOM/3. Building a SOM - Step 2.srt 19.7 kB
  • 3. ANN Intuition/6. Gradient Descent.srt 19.6 kB
  • 15. Building a RNN/13. Building a RNN - Step 11.srt 19.1 kB
  • 10. Building a CNN/4. Building a CNN - Step 1.srt 19.0 kB
  • 23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.srt 18.9 kB
  • 23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.srt 18.8 kB
  • 18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).srt 18.8 kB
  • 18. SOMs Intuition/2. How do Self-Organizing Maps Work.srt 18.7 kB
  • 15. Building a RNN/17. Building a RNN - Step 15.srt 18.1 kB
  • 3. ANN Intuition/7. Stochastic Gradient Descent.srt 18.0 kB
  • 10. Building a CNN/13. Building a CNN - Step 10.srt 17.7 kB
  • 18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).srt 17.5 kB
  • 3. ANN Intuition/3. The Activation Function.srt 17.3 kB
  • 23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.srt 16.8 kB
  • 1. Welcome to the course/4. Installing Python.srt 16.7 kB
  • 26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.srt 16.6 kB
  • 23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.srt 16.4 kB
  • 15. Building a RNN/9. Building a RNN - Step 7.srt 16.3 kB
  • 29. Data Preprocessing Template/1. Data Preprocessing - Step 1.srt 15.7 kB
  • 4. Building an ANN/12. Building an ANN - Step 8.srt 15.6 kB
  • 29. Data Preprocessing Template/2. Data Preprocessing - Step 2.srt 15.5 kB
  • 15. Building a RNN/16. Building a RNN - Step 14.srt 14.5 kB
  • 4. Building an ANN/14. Building an ANN - Step 10.srt 14.4 kB
  • 6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.srt 14.0 kB
  • 23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.srt 13.9 kB
  • 25. AutoEncoders Intuition/4. Training an Auto Encoder.srt 13.7 kB
  • 23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.srt 13.1 kB
  • 15. Building a RNN/4. Building a RNN - Step 2.srt 13.0 kB
  • 9. CNN Intuition/5. Step 1(b) - ReLU Layer.srt 12.8 kB
  • 10. Building a CNN/10. Building a CNN - Step 7.srt 12.7 kB
  • 25. AutoEncoders Intuition/6. Sparse Autoencoders.srt 12.5 kB
  • 15. Building a RNN/3. Building a RNN - Step 1.srt 12.3 kB
  • 4. Building an ANN/13. Building an ANN - Step 9.srt 12.0 kB
  • 15. Building a RNN/10. Building a RNN - Step 8.srt 11.7 kB
  • 28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.srt 11.5 kB
  • 22. Boltzmann Machine Intuition/7. Deep Belief Networks.srt 10.8 kB
  • 15. Building a RNN/5. Building a RNN - Step 3.srt 10.7 kB
  • 23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.srt 10.6 kB
  • 10. Building a CNN/9. Building a CNN - Step 6.srt 10.6 kB
  • 4. Building an ANN/3. Business Problem Description.srt 10.6 kB
  • 3. ANN Intuition/8. Backpropagation.srt 10.2 kB
  • 26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.srt 10.2 kB
  • 10. Building a CNN/8. Building a CNN - Step 5.srt 10.1 kB
  • 30. Classification Template/1. Logistic Regression Implementation - Step 1.srt 10.0 kB
  • 15. Building a RNN/12. Building a RNN - Step 10.srt 9.6 kB
  • 26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.srt 9.5 kB
  • 18. SOMs Intuition/7. Live SOM example.srt 9.4 kB
  • 20. Mega Case Study/2. Mega Case Study - Step 2.srt 9.0 kB
  • 10. Building a CNN/3. Introduction to CNNs.srt 8.8 kB
  • 9. CNN Intuition/9. Summary.srt 8.7 kB
  • 30. Classification Template/6. Classification Template.srt 8.4 kB
  • 30. Classification Template/4. Logistic Regression Implementation - Step 4.srt 8.3 kB
  • 25. AutoEncoders Intuition/5. Overcomplete hidden layers.srt 8.3 kB
  • 4. Building an ANN/11. Building an ANN - Step 7.srt 8.1 kB
  • 29. Data Preprocessing Template/7. Data Preprocessing Template.srt 8.1 kB
  • 9. CNN Intuition/2. Plan of attack.srt 7.6 kB
  • 14. RNN Intuition/7. EXTRA LSTM Variations.srt 6.9 kB
  • 20. Mega Case Study/1. Mega Case Study - Step 1.srt 6.8 kB
  • 22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.srt 6.8 kB
  • 18. SOMs Intuition/1. Plan of attack.srt 6.8 kB
  • 15. Building a RNN/11. Building a RNN - Step 9.srt 6.7 kB
  • 4. Building an ANN/7. Building an ANN - Step 3.srt 6.7 kB
  • 22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.srt 6.4 kB
  • 1. Welcome to the course/1. Updates on Udemy Reviews.srt 6.4 kB
  • 15. Building a RNN/8. Building a RNN - Step 6.srt 6.3 kB
  • 30. Classification Template/2. Logistic Regression Implementation - Step 2.srt 6.2 kB
  • 4. Building an ANN/10. Building an ANN - Step 6.srt 6.2 kB
  • 28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.srt 6.2 kB
  • 10. Building a CNN/5. Building a CNN - Step 2.srt 5.8 kB
  • 10. Building a CNN/11. Building a CNN - Step 8.srt 5.8 kB
  • 3. ANN Intuition/1. Plan of Attack.srt 5.7 kB
  • 25. AutoEncoders Intuition/7. Denoising Autoencoders.srt 5.4 kB
  • 22. Boltzmann Machine Intuition/1. Plan of attack.srt 5.3 kB
  • 30. Classification Template/3. Logistic Regression Implementation - Step 3.srt 5.1 kB
  • 25. AutoEncoders Intuition/8. Contractive Autoencoders.srt 5.0 kB
  • 14. RNN Intuition/2. Plan of attack.srt 5.0 kB
  • 18. SOMs Intuition/3. Why revisit K-Means.srt 4.9 kB
  • 25. AutoEncoders Intuition/1. Plan of attack.srt 4.8 kB
  • 4. Building an ANN/8. Building an ANN - Step 4.srt 4.6 kB
  • 23. Building a Boltzmann Machine/19. Evaluating the Boltzmann Machine.html 4.6 kB
  • 25. AutoEncoders Intuition/10. Deep Autoencoders.srt 3.9 kB
  • 9. CNN Intuition/7. Step 3 - Flattening.srt 3.9 kB
  • 1. Welcome to the course/5. How to get the dataset.srt 3.6 kB
  • 10. Building a CNN/1. How to get the dataset.srt 3.6 kB
  • 15. Building a RNN/1. How to get the dataset.srt 3.6 kB
  • 19. Building a SOM/1. How to get the dataset.srt 3.6 kB
  • 23. Building a Boltzmann Machine/1. How to get the dataset.srt 3.6 kB
  • 26. Building an AutoEncoder/1. How to get the dataset.srt 3.6 kB
  • 4. Building an ANN/2. How to get the dataset.srt 3.6 kB
  • 25. AutoEncoders Intuition/9. Stacked Autoencoders.srt 3.4 kB
  • 31. Bonus Lectures/1. YOUR SPECIAL BONUS.html 3.1 kB
  • 25. AutoEncoders Intuition/3. A Note on Biases.srt 2.8 kB
  • 26. Building an AutoEncoder/16. THANK YOU bonus video.srt 2.5 kB
  • 1. Welcome to the course/3. BONUS Learning Paths.html 2.4 kB
  • 10. Building a CNN/6. Building a CNN - Step 3.srt 2.4 kB
  • 1. Welcome to the course/6.1 DL-A-Z-Colab-Run-Instructions.ipynb.zip.zip 2.3 kB
  • 28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.srt 2.2 kB
  • 1. Welcome to the course/9. FAQBot!.html 1.8 kB
  • 16. Evaluating, Improving and Tuning the RNN/1. Evaluating the RNN.html 1.8 kB
  • 21. ------------------------- Part 5 - Boltzmann Machines -------------------------/1. Welcome to Part 5 - Boltzmann Machines.html 1.6 kB
  • 26. Building an AutoEncoder/7. Homework Challenge - Coding Exercise.html 1.6 kB
  • 4. Building an ANN/4. Installing Keras.html 1.4 kB
  • 26. Building an AutoEncoder/2. Installing PyTorch.html 1.4 kB
  • 23. Building a Boltzmann Machine/2. Installing PyTorch.html 1.4 kB
  • 4. Building an ANN/1. Prerequisites.html 1.4 kB
  • 16. Evaluating, Improving and Tuning the RNN/2. Improving the RNN.html 1.3 kB
  • 1. Welcome to the course/7. BONUS Meet Your Instructors.html 1.2 kB
  • 13. ---------------------- Part 3 - Recurrent Neural Networks ----------------------/1. Welcome to Part 3 - Recurrent Neural Networks.html 1.1 kB
  • 24. ---------------------------- Part 6 - AutoEncoders ----------------------------/1. Welcome to Part 6 - AutoEncoders.html 1.1 kB
  • Read Me.txt 1.0 kB
  • 10. Building a CNN/2. Installing Keras.html 927 Bytes
  • 15. Building a RNN/2. Installing Keras.html 927 Bytes
  • 12. Evaluating, Improving and Tuning the CNN/1. Homework Challenge - Get the gold medal.html 917 Bytes
  • 27. ------------------- Annex - Get the Machine Learning Basics -------------------/1. Annex - Get the Machine Learning Basics.html 873 Bytes
  • 11. Homework - What's that pet/1. Homework Instruction.html 838 Bytes
  • 16. Evaluating, Improving and Tuning the RNN/3. Tuning the RNN.html 693 Bytes
  • 5. Homework Challenge - Should we say goodbye to that customer/1. Homework Instruction.html 682 Bytes
  • 1. Welcome to the course/6. Colab File.html 665 Bytes
  • 28. Regression & Classification Intuition/1. What You Need for Regression & Classification.html 648 Bytes
  • 1. Welcome to the course/8. Some Additional Resources!!.html 611 Bytes
  • 2. --------------------- Part 1 - Artificial Neural Networks ---------------------/1. Welcome to Part 1 - Artificial Neural Networks.html 516 Bytes
  • 7. Homework Challenge - Put me one step down on the podium/1. Homework Instruction.html 426 Bytes
  • 9. CNN Intuition/1. What You'll Need for CNN.html 386 Bytes
  • 14. RNN Intuition/1. What You'll Need for RNN.html 366 Bytes
  • 23. Building a Boltzmann Machine/4. Same Data Preprocessing in Parts 5 and 6.html 349 Bytes
  • 26. Building an AutoEncoder/3. Same Data Preprocessing in Parts 5 and 6.html 348 Bytes
  • 17. ------------------------ Part 4 - Self Organizing Maps ------------------------/1. Welcome to Part 4 - Self Organizing Maps.html 333 Bytes
  • 8. -------------------- Part 2 - Convolutional Neural Networks --------------------/1. Welcome to Part 2 - Convolutional Neural Networks.html 323 Bytes
  • [FreeAllCourse.Com].URL 228 Bytes
  • 12. Evaluating, Improving and Tuning the CNN/2. Homework Challenge Solution - Get the gold medal.html 185 Bytes

随机展示

相关说明

本站不存储任何资源内容,只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符),并提供查询服务,是一个完全合法的搜索引擎系统。 网站不提供种子下载服务,用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责,请用户注意甄别!