深度学习：高级计算机视觉教程（GAN、SSD等！）
Deep Learning Advanced Computer Vision (GANs, SSD, +More!)深度学习：高级计算机视觉教程（英文外语教学）
├──1. Welcome
| ├──1. Introduction39.mp47.77M
| ├──1. Introduction39.srt5.05kb
| ├──2. Outline and Perspective.mp47.45M
| ├──2. Outline and Perspective.srt13.79kb
| ├──3. Where to get the code.mp446.05M
| ├──3. Where to get the code.srt19.59kb
| ├──3.1 Colab Notebooks.html0.15kb
| ├──3.2 Github Link.html0.12kb
| ├──4. How to Succeed in this Course.mp43.30M
| └──4. How to Succeed in this Course.srt6.11kb
├──10. GANs (Generative Adversarial Networks)
| ├──1. GAN Theory.mp491.06M
| ├──1. GAN Theory.srt31.94kb
| ├──2. GAN Colab Notebook.html0.24kb
| ├──3. GAN Code.mp482.29M
| └──3. GAN Code.srt23.34kb
├──11. Object Localization Project
| ├──1. Localization Introduction and Outline.mp462.90M
| ├──1. Localization Introduction and Outline.srt28.09kb
| ├──10. Localization Code (pt 4).mp413.32M
| ├──10. Localization Code (pt 4).srt3.48kb
| ├──11. Localization Code Outline (pt 5).mp443.07M
| ├──11. Localization Code Outline (pt 5).srt16.84kb
| ├──12. Localization Code (pt 5).mp459.85M
| ├──12. Localization Code (pt 5).srt16.40kb
| ├──13. Localization Code Outline (pt 6).mp433.57M
| ├──13. Localization Code Outline (pt 6).srt14.82kb
| ├──14. Localization Code (pt 6).mp456.68M
| ├──14. Localization Code (pt 6).srt15.37kb
| ├──15. Localization Code Outline (pt 7).mp420.61M
| ├──15. Localization Code Outline (pt 7).srt10.04kb
| ├──16. Localization Code (pt 7).mp477.18M
| ├──16. Localization Code (pt 7).srt24.21kb
| ├──2. Localization Code Outline (pt 1).mp441.29M
| ├──2. Localization Code Outline (pt 1).srt22.08kb
| ├──3. Object Localization Colab Notebooks.html0.77kb
| ├──4. Localization Code (pt 1).mp453.81M
| ├──4. Localization Code (pt 1).srt18.45kb
| ├──5. Localization Code Outline (pt 2).mp418.71M
| ├──5. Localization Code Outline (pt 2).srt9.74kb
| ├──6. Localization Code (pt 2).mp458.60M
| ├──6. Localization Code (pt 2).srt21.76kb
| ├──7. Localization Code Outline (pt 3).mp412.33M
| ├──7. Localization Code Outline (pt 3).srt6.78kb
| ├──8. Localization Code (pt 3).mp430.06M
| ├──8. Localization Code (pt 3).srt8.13kb
| ├──9. Localization Code Outline (pt 4).mp413.66M
| └──9. Localization Code Outline (pt 4).srt7.26kb
├──12. Keras and Tensorflow 2 Basics Review
| ├──1. (Review) Tensorflow Basics.mp481.53M
| ├──1. (Review) Tensorflow Basics.srt9.05kb
| ├──2. (Review) Tensorflow Neural Network in Code.mp497.24M
| ├──2. (Review) Tensorflow Neural Network in Code.srt8.49kb
| ├──3. (Review) Keras Discussion.mp427.64M
| ├──3. (Review) Keras Discussion.srt14.56kb
| ├──4. (Review) Keras Neural Network in Code.mp466.16M
| ├──4. (Review) Keras Neural Network in Code.srt11.48kb
| ├──5. (Review) Keras Functional API.mp438.64M
| ├──5. (Review) Keras Functional API.srt8.43kb
| ├──6. (Review) How to easily convert Keras into Tensorflow 2.0 code.mp49.81M
| └──6. (Review) How to easily convert Keras into Tensorflow 2.0 code.srt2.08kb
├──13. Setting Up Your Environment (FAQ by Student Request)
| ├──1. Windows-Focused Environment Setup 2018.mp4186.32M
| ├──1. Windows-Focused Environment Setup 2018.srt20.10kb
| ├──2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.82M
| └──2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt14.48kb
├──14. Extra Help With Python Coding for Beginners (FAQ by Student Request)
| ├──1. How to Code by Yourself (part 1).mp424.53M
| ├──1. How to Code by Yourself (part 1).srt22.75kb
| ├──2. How to Code by Yourself (part 2).mp48.64M
| ├──2. How to Code by Yourself (part 2).srt13.22kb
| ├──3. Proof that using Jupyter Notebook is the same as not using it.mp478.26M
| ├──3. Proof that using Jupyter Notebook is the same as not using it.srt14.12kb
| ├──4. Python 2 vs Python 3.mp45.47M
| └──4. Python 2 vs Python 3.srt6.05kb
├──15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
| ├──1. How to Succeed in this Course (Long Version).mp412.99M
| ├──1. How to Succeed in this Course (Long Version).srt14.66kb
| ├──2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95M
| ├──2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt31.79kb
| ├──3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp429.32M
| ├──3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt16.03kb
| ├──4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp437.62M
| └──4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt23.04kb
├──16. AppendixFAQ Finale
| ├──1. What is the Appendix (1).srt5.60kb
| ├──1. What is the Appendix.mp45.45M
| ├──1. What is the Appendix.srt3.72kb
| ├──2. BONUS Where to get discount coupons and FREE deep learning material.mp437.81M
| └──2. BONUS Where to get discount coupons and FREE deep learning material.srt12.44kb
├──2. Machine Learning Basics Review
| ├──1. What is Machine Learning.mp470.85M
| ├──1. What is Machine Learning.srt29.35kb
| ├──10. Saving and Loading a Model.mp433.86M
| ├──10. Saving and Loading a Model.srt7.90kb
| ├──11. Suggestion Box.mp416.11M
| ├──11. Suggestion Box.srt7.15kb
| ├──2. Code Preparation (Classification Theory).mp465.13M
| ├──2. Code Preparation (Classification Theory).srt32.25kb
| ├──3. Beginner's Code Preamble.mp425.11M
| ├──3. Beginner's Code Preamble.srt10.58kb
| ├──3.1 Notebooks.html0.15kb
| ├──4. Classification Notebook.mp460.47M
| ├──4. Classification Notebook.srt14.66kb
| ├──5. Code Preparation (Regression Theory).mp430.71M
| ├──5. Code Preparation (Regression Theory).srt13.73kb
| ├──6. Regression Notebook.mp464.67M
| ├──6. Regression Notebook.srt19.38kb
| ├──7. The Neuron.mp445.48M
| ├──7. The Neuron.srt19.58kb
| ├──8. How does a model learn.mp451.84M
| ├──8. How does a model learn.srt22.05kb
| ├──9. Making Predictions.mp436.85M
| └──9. Making Predictions.srt12.61kb
├──3. Artificial Neural Networks (ANN) Review
| ├──1. Artificial Neural Networks Section Introduction.mp429.85M
| ├──1. Artificial Neural Networks Section Introduction.srt12.42kb
| ├──2. Forward Propagation.mp446.75M
| ├──2. Forward Propagation.srt12.41kb
| ├──3. The Geometrical Picture.mp456.46M
| ├──3. The Geometrical Picture.srt18.39kb
| ├──4. Activation Functions.mp480.61M
| ├──4. Activation Functions.srt34.90kb
| ├──5. Multiclass Classification.mp441.41M
| ├──5. Multiclass Classification.srt17.07kb
| ├──6. How to Represent Images.mp470.49M
| ├──6. How to Represent Images.srt24.87kb
| ├──7. Code Preparation (ANN).mp450.97M
| ├──7. Code Preparation (ANN).srt25.25kb
| ├──8. ANN for Image Classification.mp447.71M
| ├──8. ANN for Image Classification.srt15.36kb
| ├──9. ANN for Regression.mp469.23M
| └──9. ANN for Regression.srt20.53kb
├──4. Convolutional Neural Networks (CNN) Review
| ├──1. What is Convolution (part 1).mp479.83M
| ├──1. What is Convolution (part 1).srt32.04kb
| ├──10. Batch Normalization.mp421.13M
| ├──10. Batch Normalization.srt10.19kb
| ├──11. Improving CIFAR-10 Results.mp472.94M
| ├──11. Improving CIFAR-10 Results.srt20.90kb
| ├──2. What is Convolution (part 2).mp422.30M
| ├──2. What is Convolution (part 2).srt10.70kb
| ├──3. What is Convolution (part 3).mp427.63M
| ├──3. What is Convolution (part 3).srt12.55kb
| ├──4. Convolution on Color Images.mp469.43M
| ├──4. Convolution on Color Images.srt32.45kb
| ├──5. CNN Architecture.mp480.68M
| ├──5. CNN Architecture.srt44.47kb
| ├──6. CNN Code Preparation.mp476.91M
| ├──6. CNN Code Preparation.srt30.67kb
| ├──7. CNN for Fashion MNIST.mp442.80M
| ├──7. CNN for Fashion MNIST.srt12.58kb
| ├──8. CNN for CIFAR-10.mp429.69M
| ├──8. CNN for CIFAR-10.srt8.65kb
| ├──9. Data Augmentation.mp434.99M
| └──9. Data Augmentation.srt17.75kb
├──5. VGG and Transfer Learning
| ├──1. VGG Section Intro.mp42.69M
| ├──1. VGG Section Intro.srt5.84kb
| ├──2. What's so special about VGG.mp412.19M
| ├──2. What's so special about VGG.srt14.29kb
| ├──3. Transfer Learning.mp438.12M
| ├──3. Transfer Learning.srt16.40kb
| ├──4. Relationship to Greedy Layer-Wise Pretraining.mp43.88M
| ├──4. Relationship to Greedy Layer-Wise Pretraining.srt4.16kb
| ├──5. Getting the data.mp41.77M
| ├──5. Getting the data.srt4.40kb
| ├──6. Code pt 1.mp411.51M
| ├──6. Code pt 1.srt19.43kb
| ├──7. Code pt 2.mp48.56M
| ├──7. Code pt 2.srt7.48kb
| ├──8. Code pt 3.mp44.22M
| ├──8. Code pt 3.srt6.80kb
| ├──9. VGG Section Summary.mp43.15M
| └──9. VGG Section Summary.srt3.28kb
├──6. ResNet (and Inception)
| ├──1. ResNet Section Intro.mp42.82M
| ├──1. ResNet Section Intro.srt5.89kb
| ├──10. Building ResNet - Putting it all together.mp45.91M
| ├──10. Building ResNet - Putting it all together.srt7.91kb
| ├──11. Exercise Apply ResNet.mp42.07M
| ├──11. Exercise Apply ResNet.srt2.43kb
| ├──12. Applying ResNet.mp43.59M
| ├──12. Applying ResNet.srt4.84kb
| ├──13. 1x1 Convolutions.mp43.11M
| ├──13. 1x1 Convolutions.srt7.75kb
| ├──14. Optional Inception.mp45.39M
| ├──14. Optional Inception.srt13.62kb
| ├──15. Different sized images using the same network.mp47.41M
| ├──15. Different sized images using the same network.srt8.69kb
| ├──16. ResNet Section Summary.mp44.19M
| ├──16. ResNet Section Summary.srt4.53kb
| ├──2. ResNet Architecture.mp410.39M
| ├──2. ResNet Architecture.srt25.67kb
| ├──3. Building ResNet - Strategy.mp42.66M
| ├──3. Building ResNet - Strategy.srt4.68kb
| ├──4. Uh-oh! What Happens if the Implementation Changes.mp425.34M
| ├──4. Uh-oh! What Happens if the Implementation Changes.srt11.24kb
| ├──5. Building ResNet - Conv Block Details.mp46.18M
| ├──5. Building ResNet - Conv Block Details.srt7.04kb
| ├──6. Building ResNet - Conv Block Code.mp48.97M
| ├──6. Building ResNet - Conv Block Code.srt12.24kb
| ├──7. Building ResNet - Identity Block Details.mp42.38M
| ├──7. Building ResNet - Identity Block Details.srt2.69kb
| ├──8. Building ResNet - First Few Layers.mp44.03M
| ├──8. Building ResNet - First Few Layers.srt4.74kb
| ├──9. Building ResNet - First Few Layers (Code).mp410.31M
| └──9. Building ResNet - First Few Layers (Code).srt7.49kb
├──7. Object Detection (SSDRetinaNet)
| ├──1. SSD Section Intro.mp45.69M
| ├──1. SSD Section Intro.srt9.83kb
| ├──10. RetinaNet with Custom Dataset (pt 2).mp460.52M
| ├──10. RetinaNet with Custom Dataset (pt 2).srt19.31kb
| ├──11. RetinaNet with Custom Dataset (pt 3).mp461.81M
| ├──11. RetinaNet with Custom Dataset (pt 3).srt12.66kb
| ├──12. Optional Intersection over Union & Non-max Suppression.mp44.59M
| ├──12. Optional Intersection over Union & Non-max Suppression.srt9.73kb
| ├──13. SSD Section Summary.mp42.83M
| ├──13. SSD Section Summary.srt5.50kb
| ├──2. Object Localization.mp45.69M
| ├──2. Object Localization.srt12.50kb
| ├──3. What is Object Detection.mp44.79M
| ├──3. What is Object Detection.srt5.68kb
| ├──4. How would you find an object in an image.mp47.85M
| ├──4. How would you find an object in an image.srt16.34kb
| ├──5. The Problem of Scale.mp44.16M
| ├──5. The Problem of Scale.srt7.14kb
| ├──6. The Problem of Shape.mp43.59M
| ├──6. The Problem of Shape.srt7.26kb
| ├──7. 2020 Update - More Fun and Excitement.mp434.59M
| ├──7. 2020 Update - More Fun and Excitement.srt12.97kb
| ├──8. Using Pretrained RetinaNet.mp488.23M
| ├──8. Using Pretrained RetinaNet.srt23.15kb
| ├──8.1 Notebooks.html0.15kb
| ├──9. RetinaNet with Custom Dataset (pt 1).mp426.60M
| └──9. RetinaNet with Custom Dataset (pt 1).srt9.50kb
├──8. Neural Style Transfer
| ├──1. Style Transfer Section Intro.mp42.91M
| ├──1. Style Transfer Section Intro.srt5.95kb
| ├──2. Style Transfer Theory.mp419.94M
| ├──2. Style Transfer Theory.srt22.38kb
| ├──3. Optimizing the Loss.mp47.24M
| ├──3. Optimizing the Loss.srt16.07kb
| ├──4. Code pt 1.mp49.46M
| ├──4. Code pt 1.srt14.97kb
| ├──5. Code pt 2.mp415.71M
| ├──5. Code pt 2.srt14.26kb
| ├──6. Code pt 3.mp45.74M
| ├──6. Code pt 3.srt6.90kb
| ├──7. Style Transfer Section Summary.mp42.50M
| └──7. Style Transfer Section Summary.srt4.60kb
└──9. Class Activation Maps
| ├──1. Class Activation Maps (Theory).mp453.42M
| ├──1. Class Activation Maps (Theory).srt13.88kb
| ├──2. Class Activation Maps (Code).mp4104.76M
| └──2. Class Activation Maps (Code).srt15.57kb
**** Hidden Message *****
:) 强烈支持楼主ing…… 激动人心，无法言表！ : 深度学习：高级计算机视觉教程（GAN、SSD等！） [ 淡定，淡定，淡定…… 强烈支持楼主ing…… 强烈支持楼主ing…… 强烈支持楼主ing…… 强烈支持楼主ing……