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[UdemyCourseDownloader] Deep Learning Advanced Computer Vision

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种子名称: [UdemyCourseDownloader] Deep Learning Advanced Computer Vision
文件类型: 视频
文件数目: 67个文件
文件大小: 1.27 GB
收录时间: 2019-12-5 16:13
已经下载: 3
资源热度: 159
最近下载: 2024-12-17 13:18

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[UdemyCourseDownloader] Deep Learning Advanced Computer Vision.torrent
  • 9. Appendix/2. Windows-Focused Environment Setup 2018.mp4186.32MB
  • 1. Welcome/1. Introduction.mp47.77MB
  • 1. Welcome/2. Outline and Perspective.mp47.46MB
  • 1. Welcome/3. How to Succeed in this Course.mp43.31MB
  • 2. Review/1. Review of CNNs.mp418.5MB
  • 2. Review/2. Where to get the code and data.mp42.18MB
  • 2. Review/3. Fashion MNIST.mp43.29MB
  • 2. Review/4. Review of CNNs in Code.mp47.61MB
  • 3. VGG and Transfer Learning/1. VGG Section Intro.mp42.7MB
  • 3. VGG and Transfer Learning/2. What's so special about VGG.mp412.2MB
  • 3. VGG and Transfer Learning/3. Transfer Learning.mp438.13MB
  • 3. VGG and Transfer Learning/4. Relationship to Greedy Layer-Wise Pretraining.mp43.89MB
  • 3. VGG and Transfer Learning/5. Getting the data.mp41.77MB
  • 3. VGG and Transfer Learning/6. Code pt 1.mp411.52MB
  • 3. VGG and Transfer Learning/7. Code pt 2.mp48.57MB
  • 3. VGG and Transfer Learning/8. Code pt 3.mp44.21MB
  • 3. VGG and Transfer Learning/9. VGG Section Summary.mp43.16MB
  • 4. ResNet (and Inception)/1. ResNet Section Intro.mp42.82MB
  • 4. ResNet (and Inception)/2. ResNet Architecture.mp410.4MB
  • 4. ResNet (and Inception)/3. Building ResNet - Strategy.mp42.67MB
  • 4. ResNet (and Inception)/4. Building ResNet - Conv Block Details.mp46.19MB
  • 4. ResNet (and Inception)/5. Building ResNet - Conv Block Code.mp48.98MB
  • 4. ResNet (and Inception)/6. Building ResNet - Identity Block Details.mp42.37MB
  • 4. ResNet (and Inception)/7. Building ResNet - First Few Layers.mp44.03MB
  • 4. ResNet (and Inception)/8. Building ResNet - First Few Layers (Code).mp410.31MB
  • 4. ResNet (and Inception)/9. Building ResNet - Putting it all together.mp45.92MB
  • 4. ResNet (and Inception)/10. Exercise Apply ResNet.mp42.08MB
  • 4. ResNet (and Inception)/11. Applying ResNet.mp43.6MB
  • 4. ResNet (and Inception)/12. 1x1 Convolutions.mp43.11MB
  • 4. ResNet (and Inception)/13. Optional Inception.mp45.39MB
  • 4. ResNet (and Inception)/14. Different sized images using the same network.mp47.42MB
  • 4. ResNet (and Inception)/15. ResNet Section Summary.mp44.19MB
  • 5. Object Detection (SSD)/1. SSD Section Intro.mp45.7MB
  • 5. Object Detection (SSD)/2. Object Localization.mp45.69MB
  • 5. Object Detection (SSD)/3. What is Object Detection.mp44.79MB
  • 5. Object Detection (SSD)/4. How would you find an object in an image.mp47.85MB
  • 5. Object Detection (SSD)/5. The Problem of Scale.mp44.16MB
  • 5. Object Detection (SSD)/6. The Problem of Shape.mp43.6MB
  • 5. Object Detection (SSD)/7. SSD in Tensorflow.mp417.42MB
  • 5. Object Detection (SSD)/8. Modifying SSD to work on Video.mp424.79MB
  • 5. Object Detection (SSD)/9. Optional Intersection over Union & Non-max Suppression.mp44.59MB
  • 5. Object Detection (SSD)/10. SSD Section Summary.mp42.82MB
  • 6. Neural Style Transfer/1. Style Transfer Section Intro.mp42.92MB
  • 6. Neural Style Transfer/2. Style Transfer Theory.mp419.94MB
  • 6. Neural Style Transfer/3. Optimizing the Loss.mp47.25MB
  • 6. Neural Style Transfer/4. Code pt 1.mp49.46MB
  • 6. Neural Style Transfer/5. Code pt 2.mp415.72MB
  • 6. Neural Style Transfer/6. Code pt 3.mp45.74MB
  • 6. Neural Style Transfer/7. Style Transfer Section Summary.mp42.51MB
  • 7. Bonus Class Activation Maps/1. Class Activation Maps (Theory).mp453.42MB
  • 7. Bonus Class Activation Maps/2. Class Activation Maps (Code).mp4104.76MB
  • 8. Basics Review/1. (Review) Tensorflow Basics.mp481.54MB
  • 8. Basics Review/2. (Review) Tensorflow Neural Network in Code.mp497.24MB
  • 8. Basics Review/3. (Review) Keras Discussion.mp427.64MB
  • 8. Basics Review/4. (Review) Keras Neural Network in Code.mp466.16MB
  • 8. Basics Review/5. (Review) Keras Functional API.mp438.65MB
  • 9. Appendix/1. What is the Appendix.mp45.45MB
  • 9. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.82MB
  • 9. Appendix/4. How to Succeed in this Course (Long Version).mp413MB
  • 9. Appendix/5. How to Code by Yourself (part 1).mp424.53MB
  • 9. Appendix/6. How to Code by Yourself (part 2).mp48.64MB
  • 9. Appendix/7. Proof that using Jupyter Notebook is the same as not using it.mp478.27MB
  • 9. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.96MB
  • 9. Appendix/9. Where to get discount coupons and FREE deep learning material.mp43.38MB
  • 9. Appendix/10. Python 2 vs Python 3.mp45.47MB
  • 9. Appendix/11. What order should I take your courses in (part 1).mp429.33MB
  • 9. Appendix/12. What order should I take your courses in (part 2).mp437.62MB