【书籍】Grokking Deep Learning

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阅读进度：

• 1.Introducing deep learning: why you should learn it?
• 2.Fundamental concepts: how do machines learn?
• 3.Introduction to neural prediction: forward propagation
• 4.Introduction to neural learning: gradient descent
• 5.Learning multiple weights at a time
• 6.Building your first deep neural network: introduction to backpropagation
• 7.How to picture neural networks: in your head and on paper
• 8.Learning signal and ignoring noise: introduction to regularization and batching
• 9.Modeling probabilities and nonlinearities: activation functions
• 10.Neural learning about edges and corners: intro to convolutional neural networks
• 11.Neural networks that understand language: king – man + woman == ?
• 12.Neural networks that write like Shakespeare: recurrent layers for variable-length data
• 13.Introducing automatic optimization: let’s build a deep learning framework
• 14.Learning to write like Shakespeare: long short-term memory
• 15.Deep learning on unseen data: introducing federated learning
• 16.Where to go from here: a brief guide