TensorFlow2.x 学习笔记(二)回归问题&分类问题

$f_{\theta }:x\to y$
$y$通常可以分为两类：离散或连续
连续时为回归问题
linear regression
loss function
gradient descent
loss surface
convex Optimization

• linear regression
  • linear Regression
  • logistic Regression
  • Classification

回归问题实战

• 线性回归

• 离散值预测

  • Image Classificaton

    • ImageNet
    • MNIST
      • Hand-written Digits Recognition
      • 7000 images per category
      • train/test:60k/10k

  • Input and Output

    • flatten
      • matrix to vector
    • one-hot
      • $\sum p(y=i|x)=1$

• Regression vs Classification

  • $y\in R^d$
  • $y[i]=p(y=i|x)$

• unlinear

  • ReLU

• hidden layer stack

• Loss

  • MSE(out, label)
  • Cross Entropy

• GPU speedup!

• Enjoy MNIST!