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Lecture I: Introduction of Deep Learning

DL 统共分三步，

• Step 1: Desgin a Network Struture (a set of functions with params $\theta$θ, linear/non-linear)
• Step 2: Set Learning Target (loss function $L$L)
• Step 3: Dive into learning! (pick the best group of $\theta$θ that minimize $L$L)
  
  DL 胜任的工作:
  

Human Brains

AI Neural Network

A typical Fully Connected Network

Loss

Total Loss

• Gradient Descent
  

• Backpropagation is an efficient way to compute $\partial L / \partial w$∂L/∂w
  

Lecture II: Tips for Training Deep Neural Network

Lecture III: Variants of Neural Network

Lecture IV: Next Wave