【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

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