Deep Learning 1: Overview

Five Questions Data Science Answers:

https://brohrer.github.io/five_questions_data_science_answers.html
1. Is this A or B?
2. Is this weird?
3. How much/how many?
4. How is it organized?
5. What should I do next?

Resources:

1.Neural Networks and Deep Learning: http://neuralnetworksanddeeplearning.com/
  version in Simplified Mandarin is also available
2.Data Science and Robots Blog: https://brohrer.github.io/blog.html?from=timeline&isappinstalled=0
  version in Simplified Mandarin is also available

3.CS231n: Convolutional Neural Networks for Visual Recognition： http://cs231n.stanford.edu/

4.http://colah.github.io/

5.如何选择 Microsoft Azure 机器学习的算法: https://docs.microsoft.com/zh-cn/azure/machine-learning/studio/algorithm-choice

6.Alex Krizhevsky: http://www.cs.toronto.edu/~kriz/