TensorFlow for Deep Learning(Early Release) 无水印pdf
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2017-10-04
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1. 1. Introduction to Deep Learning
1. Machine Learning eats Computer Science
2. Deep Learning Primitives
1. Fully Connected Layer
2. Convolutional Layer
3. Recurrent Neural Network (RNN) Layers
4. Long Short-Term Memory (LSTM) Cells
3. Deep Learning Zoo
1. LeNet
2. AlexNet
3. ResNet
4. Neural Captioning Model
5. Google Neural Machine Translation
6. One shot models
7. AlphaGo
8. Generative Adversarial Networks
9. Neural Turing Machines
4. Deep Learning Frameworks
5. Empirical Learning
2. 2. Introduction to Tensorflow Primitives
1. Introducing Tensors
1. Scalars, Vectors, and Matrices
2. Matrix Mathematics
3. Tensors
4. Tensors in physics.
5. Mathematical Asides
2. Basic Computations in Tensorflow
1. Initializing Constant Tensors.
2. Sampling Random Tensors
3. Tensor Addition and Scaling
4. Matrix Operations
5. Tensor Shape Manipulations
6. Introduction to Broadcasting
7. Tensorflow Graphs
8. Tensorflow Variables
3. Review
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