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1. What is Convolution (part 1).mp4
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10. Building ResNet - Putting it all together.mp4
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16. ResNet Section Summary.mp4
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2. (Review) Tensorflow Neural Network in Code.mp4
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2. BONUS Where to get discount coupons and FREE deep learning material.mp4
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2. Code Preparation (Classification Theory).mp4
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2. Forward Propagation.mp4
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2. GAN Colab Notebook.html
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2. How to Code by Yourself (part 2).mp4
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2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
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2. Style Transfer Theory.mp4
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2. What is Convolution (part 2).mp4
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3. (Review) Keras Discussion.mp4
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3. Building ResNet - Strategy.mp4
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3. GAN Code.mp4
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3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
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3. Object Localization Colab Notebooks.html
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3. Optimizing the Loss.mp4
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3. Proof that using Jupyter Notebook is the same as not using it.mp4
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3. What is Convolution (part 3).mp4
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3. What is Object Detection.mp4
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3. Where to get the code.mp4
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3.1 Colab Notebooks.html
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3.2 Github Link.html
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4. (Review) Keras Neural Network in Code.mp4
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4. Activation Functions.mp4
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4. Convolution on Color Images.mp4
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4. How to Succeed in this Course.mp4
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4. How would you find an object in an image.mp4
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4. Localization Code (pt 1).mp4
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4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
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4. Python 2 vs Python 3.mp4
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4. Relationship to Greedy Layer-Wise Pretraining.mp4
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4. Uh-oh! What Happens if the Implementation Changes.mp4
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5. (Review) Keras Functional API.mp4
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5. CNN Architecture.mp4
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5. Multiclass Classification.mp4
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5. The Problem of Scale.mp4
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6. (Review) How to easily convert Keras into Tensorflow 2.0 code.mp4
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6. How to Represent Images.mp4
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6. Localization Code (pt 2).mp4
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6. Regression Notebook.mp4
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6. The Problem of Shape.mp4
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7. 2020 Update - More Fun and Excitement.mp4
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7. Building ResNet - Identity Block Details.mp4
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7. CNN for Fashion MNIST.mp4
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7. Code Preparation (ANN).mp4
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7. Style Transfer Section Summary.mp4
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7. The Neuron.mp4
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8. ANN for Image Classification.mp4
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8. Building ResNet - First Few Layers.mp4
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8. CNN for CIFAR-10.mp4
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29.7 MB
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8. CNN for CIFAR-10.srt
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8. Code pt 3.mp4
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4.2 MB
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8. Code pt 3.srt
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8. How does a model learn.mp4
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51.8 MB
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8. How does a model learn.srt
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8. Localization Code (pt 3).mp4
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30.1 MB
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8. Localization Code (pt 3).srt
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8. Using Pretrained RetinaNet.mp4
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88.2 MB
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8. Using Pretrained RetinaNet.srt
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8.1 Notebooks.html
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9. ANN for Regression.mp4
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69.2 MB
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9. ANN for Regression.srt
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9. Building ResNet - First Few Layers (Code).mp4
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9. Building ResNet - First Few Layers (Code).srt
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9. Data Augmentation.mp4
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9. Data Augmentation.srt
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9. Localization Code Outline (pt 4).mp4
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9. Localization Code Outline (pt 4).srt
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9. Making Predictions.mp4
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9. Making Predictions.srt
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9. RetinaNet with Custom Dataset (pt 1).mp4
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26.6 MB
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9. RetinaNet with Custom Dataset (pt 1).srt
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9. VGG Section Summary.mp4
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READ_ME.txt
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