【资源介绍】：
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）
推荐学习《深度学习高级计算机视觉（GANs、SSD等）》！这个课程涵盖了计算机视觉领域的高级主题，如生成式对抗网络（GANs）和单发多框检测器（SSD）。学习这些技能可以让你更好地处理图像数据和进行视觉分析。
理解它。但现在，我们没有必要一步步实现所有这些高级应用程序，因为我们可以使用现成的库和框架。所以让我们开始探索这个激动人心的领域，看看我们能创造出什么样的东西！
【资源目录】：
├──1. Welcome
| ├──1. Introduction39.mp4 7.77M
| ├──1. Introduction39.srt 5.05kb
| ├──2. Outline and Perspective.mp4 7.45M
| ├──2. Outline and Perspective.srt 13.79kb
| ├──3. Where to get the code.mp4 46.05M
| ├──3. Where to get the code.srt 19.59kb
| ├──3.1 Colab Notebooks.html 0.15kb
| ├──3.2 Github Link.html 0.12kb
| ├──4. How to Succeed in this Course.mp4 3.30M
| └──4. How to Succeed in this Course.srt 6.11kb
├──10. GANs (Generative Adversarial Networks)
| ├──1. GAN Theory.mp4 91.06M
| ├──1. GAN Theory.srt 31.94kb
| ├──2. GAN Colab Notebook.html 0.24kb
| ├──3. GAN Code.mp4 82.29M
| └──3. GAN Code.srt 23.34kb
├──11. Object Localization Project
| ├──1. Localization Introduction and Outline.mp4 62.90M
| ├──1. Localization Introduction and Outline.srt 28.09kb
| ├──10. Localization Code (pt 4).mp4 13.32M
| ├──10. Localization Code (pt 4).srt 3.48kb
| ├──11. Localization Code Outline (pt 5).mp4 43.07M
| ├──11. Localization Code Outline (pt 5).srt 16.84kb
| ├──12. Localization Code (pt 5).mp4 59.85M
| ├──12. Localization Code (pt 5).srt 16.40kb
| ├──13. Localization Code Outline (pt 6).mp4 33.57M
| ├──13. Localization Code Outline (pt 6).srt 14.82kb
| ├──14. Localization Code (pt 6).mp4 56.68M
| ├──14. Localization Code (pt 6).srt 15.37kb
| ├──15. Localization Code Outline (pt 7).mp4 20.61M
| ├──15. Localization Code Outline (pt 7).srt 10.04kb
| ├──16. Localization Code (pt 7).mp4 77.18M
| ├──16. Localization Code (pt 7).srt 24.21kb
| ├──2. Localization Code Outline (pt 1).mp4 41.29M
| ├──2. Localization Code Outline (pt 1).srt 22.08kb
| ├──3. Object Localization Colab Notebooks.html 0.77kb
| ├──4. Localization Code (pt 1).mp4 53.81M
| ├──4. Localization Code (pt 1).srt 18.45kb
| ├──5. Localization Code Outline (pt 2).mp4 18.71M
| ├──5. Localization Code Outline (pt 2).srt 9.74kb
| ├──6. Localization Code (pt 2).mp4 58.60M
| ├──6. Localization Code (pt 2).srt 21.76kb
| ├──7. Localization Code Outline (pt 3).mp4 12.33M
| ├──7. Localization Code Outline (pt 3).srt 6.78kb
| ├──8. Localization Code (pt 3).mp4 30.06M
| ├──8. Localization Code (pt 3).srt 8.13kb
| ├──9. Localization Code Outline (pt 4).mp4 13.66M
| └──9. Localization Code Outline (pt 4).srt 7.26kb
├──12. Keras and Tensorflow 2 Basics Review
| ├──1. (Review) Tensorflow Basics.mp4 81.53M
| ├──1. (Review) Tensorflow Basics.srt 9.05kb
| ├──2. (Review) Tensorflow Neural Network in Code.mp4 97.24M
| ├──2. (Review) Tensorflow Neural Network in Code.srt 8.49kb
| ├──3. (Review) Keras Discussion.mp4 27.64M
| ├──3. (Review) Keras Discussion.srt 14.56kb
| ├──4. (Review) Keras Neural Network in Code.mp4 66.16M
| ├──4. (Review) Keras Neural Network in Code.srt 11.48kb
| ├──5. (Review) Keras Functional API.mp4 38.64M
| ├──5. (Review) Keras Functional API.srt 8.43kb
| ├──6. (Review) How to easily convert Keras into Tensorflow 2.0 code.mp4 9.81M
| └──6. (Review) How to easily convert Keras into Tensorflow 2.0 code.srt 2.08kb
├──13. Setting Up Your Environment (FAQ by Student Request)
| ├──1. Windows-Focused Environment Setup 2018.mp4 186.32M
| ├──1. Windows-Focused Environment Setup 2018.srt 20.10kb
| ├──2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.82M
| └──2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.48kb
├──14. Extra Help With Python Coding for Beginners (FAQ by Student Request)
| ├──1. How to Code by Yourself (part 1).mp4 24.53M
| ├──1. How to Code by Yourself (part 1).srt 22.75kb
| ├──2. How to Code by Yourself (part 2).mp4 8.64M
| ├──2. How to Code by Yourself (part 2).srt 13.22kb
| ├──3. Proof that using Jupyter Notebook is the same as not using it.mp4 78.26M
| ├──3. Proof that using Jupyter Notebook is the same as not using it.srt 14.12kb
| ├──4. Python 2 vs Python 3.mp4 5.47M
| └──4. Python 2 vs Python 3.srt 6.05kb
├──15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
| ├──1. How to Succeed in this Course (Long Version).mp4 12.99M
| ├──1. How to Succeed in this Course (Long Version).srt 14.66kb
| ├──2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 38.95M
| ├──2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.79kb
| ├──3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.32M
| ├──3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 16.03kb
| ├──4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.62M
| └──4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 23.04kb
├──16. Appendix FAQ Finale
| ├──1. What is the Appendix (1).srt 5.60kb
| ├──1. What is the Appendix.mp4 5.45M
| ├──1. What is the Appendix.srt 3.72kb
| ├──2. BONUS Where to get discount coupons and FREE deep learning material.mp4 37.81M
| └──2. BONUS Where to get discount coupons and FREE deep learning material.srt 12.44kb
├──2. Machine Learning Basics Review
| ├──1. What is Machine Learning.mp4 70.85M
| ├──1. What is Machine Learning.srt 29.35kb
| ├──10. Saving and Loading a Model.mp4 33.86M
| ├──10. Saving and Loading a Model.srt 7.90kb
| ├──11. Suggestion Box.mp4 16.11M
| ├──11. Suggestion Box.srt 7.15kb
| ├──2. Code Preparation (Classification Theory).mp4 65.13M
| ├──2. Code Preparation (Classification Theory).srt 32.25kb
| ├──3. Beginner’s Code Preamble.mp4 25.11M
| ├──3. Beginner’s Code Preamble.srt 10.58kb
| ├──3.1 Notebooks.html 0.15kb
| ├──4. Classification Notebook.mp4 60.47M
| ├──4. Classification Notebook.srt 14.66kb
| ├──5. Code Preparation (Regression Theory).mp4 30.71M
| ├──5. Code Preparation (Regression Theory).srt 13.73kb
| ├──6. Regression Notebook.mp4 64.67M
| ├──6. Regression Notebook.srt 19.38kb
| ├──7. The Neuron.mp4 45.48M
| ├──7. The Neuron.srt 19.58kb
| ├──8. How does a model learn.mp4 51.84M
| ├──8. How does a model learn.srt 22.05kb
| ├──9. Making Predictions.mp4 36.85M
| └──9. Making Predictions.srt 12.61kb
├──3. Artificial Neural Networks (ANN) Review
| ├──1. Artificial Neural Networks Section Introduction.mp4 29.85M
| ├──1. Artificial Neural Networks Section Introduction.srt 12.42kb
| ├──2. Forward Propagation.mp4 46.75M
| ├──2. Forward Propagation.srt 12.41kb
| ├──3. The Geometrical Picture.mp4 56.46M
| ├──3. The Geometrical Picture.srt 18.39kb
| ├──4. Activation Functions.mp4 80.61M
| ├──4. Activation Functions.srt 34.90kb
| ├──5. Multiclass Classification.mp4 41.41M
| ├──5. Multiclass Classification.srt 17.07kb
| ├──6. How to Represent Images.mp4 70.49M
| ├──6. How to Represent Images.srt 24.87kb
| ├──7. Code Preparation (ANN).mp4 50.97M
| ├──7. Code Preparation (ANN).srt 25.25kb
| ├──8. ANN for Image Classification.mp4 47.71M
| ├──8. ANN for Image Classification.srt 15.36kb
| ├──9. ANN for Regression.mp4 69.23M
| └──9. ANN for Regression.srt 20.53kb
├──4. Convolutional Neural Networks (CNN) Review
| ├──1. What is Convolution (part 1).mp4 79.83M
| ├──1. What is Convolution (part 1).srt 32.04kb
| ├──10. Batch Normalization.mp4 21.13M
| ├──10. Batch Normalization.srt 10.19kb
| ├──11. Improving CIFAR-10 Results.mp4 72.94M
| ├──11. Improving CIFAR-10 Results.srt 20.90kb
| ├──2. What is Convolution (part 2).mp4 22.30M
| ├──2. What is Convolution (part 2).srt 10.70kb
| ├──3. What is Convolution (part 3).mp4 27.63M
| ├──3. What is Convolution (part 3).srt 12.55kb
| ├──4. Convolution on Color Images.mp4 69.43M
| ├──4. Convolution on Color Images.srt 32.45kb
| ├──5. CNN Architecture.mp4 80.68M
| ├──5. CNN Architecture.srt 44.47kb
| ├──6. CNN Code Preparation.mp4 76.91M
| ├──6. CNN Code Preparation.srt 30.67kb
| ├──7. CNN for Fashion MNIST.mp4 42.80M
| ├──7. CNN for Fashion MNIST.srt 12.58kb
| ├──8. CNN for CIFAR-10.mp4 29.69M
| ├──8. CNN for CIFAR-10.srt 8.65kb
| ├──9. Data Augmentation.mp4 34.99M
| └──9. Data Augmentation.srt 17.75kb
├──5. VGG and Transfer Learning
| ├──1. VGG Section Intro.mp4 2.69M
| ├──1. VGG Section Intro.srt 5.84kb
| ├──2. What’s so special about VGG.mp4 12.19M
| ├──2. What’s so special about VGG.srt 14.29kb
| ├──3. Transfer Learning.mp4 38.12M
| ├──3. Transfer Learning.srt 16.40kb
| ├──4. Relationship to Greedy Layer-Wise Pretraining.mp4 3.88M
| ├──4. Relationship to Greedy Layer-Wise Pretraining.srt 4.16kb
| ├──5. Getting the data.mp4 1.77M
| ├──5. Getting the data.srt 4.40kb
| ├──6. Code pt 1.mp4 11.51M
| ├──6. Code pt 1.srt 19.43kb
| ├──7. Code pt 2.mp4 8.56M
| ├──7. Code pt 2.srt 7.48kb
| ├──8. Code pt 3.mp4 4.22M
| ├──8. Code pt 3.srt 6.80kb
| ├──9. VGG Section Summary.mp4 3.15M
| └──9. VGG Section Summary.srt 3.28kb
├──6. ResNet (and Inception)
| ├──1. ResNet Section Intro.mp4 2.82M
| ├──1. ResNet Section Intro.srt 5.89kb
| ├──10. Building ResNet – Putting it all together.mp4 5.91M
| ├──10. Building ResNet – Putting it all together.srt 7.91kb
| ├──11. Exercise Apply ResNet.mp4 2.07M
| ├──11. Exercise Apply ResNet.srt 2.43kb
| ├──12. Applying ResNet.mp4 3.59M
| ├──12. Applying ResNet.srt 4.84kb
| ├──13. 1×1 Convolutions.mp4 3.11M
| ├──13. 1×1 Convolutions.srt 7.75kb
| ├──14. Optional Inception.mp4 5.39M
| ├──14. Optional Inception.srt 13.62kb
| ├──15. Different sized images using the same network.mp4 7.41M
| ├──15. Different sized images using the same network.srt 8.69kb
| ├──16. ResNet Section Summary.mp4 4.19M
| ├──16. ResNet Section Summary.srt 4.53kb
| ├──2. ResNet Architecture.mp4 10.39M
| ├──2. ResNet Architecture.srt 25.67kb
| ├──3. Building ResNet – Strategy.mp4 2.66M
| ├──3. Building ResNet – Strategy.srt 4.68kb
| ├──4. Uh-oh! What Happens if the Implementation Changes.mp4 25.34M
| ├──4. Uh-oh! What Happens if the Implementation Changes.srt 11.24kb
| ├──5. Building ResNet – Conv Block Details.mp4 6.18M
| ├──5. Building ResNet – Conv Block Details.srt 7.04kb
| ├──6. Building ResNet – Conv Block Code.mp4 8.97M
| ├──6. Building ResNet – Conv Block Code.srt 12.24kb
| ├──7. Building ResNet – Identity Block Details.mp4 2.38M
| ├──7. Building ResNet – Identity Block Details.srt 2.69kb
| ├──8. Building ResNet – First Few Layers.mp4 4.03M
| ├──8. Building ResNet – First Few Layers.srt 4.74kb
| ├──9. Building ResNet – First Few Layers (Code).mp4 10.31M
| └──9. Building ResNet – First Few Layers (Code).srt 7.49kb
├──7. Object Detection (SSD RetinaNet)
| ├──1. SSD Section Intro.mp4 5.69M
| ├──1. SSD Section Intro.srt 9.83kb
| ├──10. RetinaNet with Custom Dataset (pt 2).mp4 60.52M
| ├──10. RetinaNet with Custom Dataset (pt 2).srt 19.31kb
| ├──11. RetinaNet with Custom Dataset (pt 3).mp4 61.81M
| ├──11. RetinaNet with Custom Dataset (pt 3).srt 12.66kb
| ├──12. Optional Intersection over Union & Non-max Suppression.mp4 4.59M
| ├──12. Optional Intersection over Union & Non-max Suppression.srt 9.73kb
| ├──13. SSD Section Summary.mp4 2.83M
| ├──13. SSD Section Summary.srt 5.50kb
| ├──2. Object Localization.mp4 5.69M
| ├──2. Object Localization.srt 12.50kb
| ├──3. What is Object Detection.mp4 4.79M
| ├──3. What is Object Detection.srt 5.68kb
| ├──4. How would you find an object in an image.mp4 7.85M
| ├──4. How would you find an object in an image.srt 16.34kb
| ├──5. The Problem of Scale.mp4 4.16M
| ├──5. The Problem of Scale.srt 7.14kb
| ├──6. The Problem of Shape.mp4 3.59M
| ├──6. The Problem of Shape.srt 7.26kb
| ├──7. 2020 Update – More Fun and Excitement.mp4 34.59M
| ├──7. 2020 Update – More Fun and Excitement.srt 12.97kb
| ├──8. Using Pretrained RetinaNet.mp4 88.23M
| ├──8. Using Pretrained RetinaNet.srt 23.15kb
| ├──8.1 Notebooks.html 0.15kb
| ├──9. RetinaNet with Custom Dataset (pt 1).mp4 26.60M
| └──9. RetinaNet with Custom Dataset (pt 1).srt 9.50kb
├──8. Neural Style Transfer
| ├──1. Style Transfer Section Intro.mp4 2.91M
| ├──1. Style Transfer Section Intro.srt 5.95kb
| ├──2. Style Transfer Theory.mp4 19.94M
| ├──2. Style Transfer Theory.srt 22.38kb
| ├──3. Optimizing the Loss.mp4 7.24M
| ├──3. Optimizing the Loss.srt 16.07kb
| ├──4. Code pt 1.mp4 9.46M
| ├──4. Code pt 1.srt 14.97kb
| ├──5. Code pt 2.mp4 15.71M
| ├──5. Code pt 2.srt 14.26kb
| ├──6. Code pt 3.mp4 5.74M
| ├──6. Code pt 3.srt 6.90kb
| ├──7. Style Transfer Section Summary.mp4 2.50M
| └──7. Style Transfer Section Summary.srt 4.60kb
└──9. Class Activation Maps
| ├──1. Class Activation Maps (Theory).mp4 53.42M
| ├──1. Class Activation Maps (Theory).srt 13.88kb
| ├──2. Class Activation Maps (Code).mp4 104.76M
| └──2. Class Activation Maps (Code).srt 15.57kb
