#!/usr/bin/env python
# coding: utf-8

# # "AlphaGo - Mastering the game of Go with deep neural networks and tree search"
# > "This post is from Deepmind and OpenAI papers series, which I try to summarize and take some notes from some interesting papers from Deepmind and OpenAI. Here I will start with AlphaGo, which tries to combine the Monte Carlo Tree Search algorithm with deep learning to play Go."
# 
# - toc:true
# - branch: master
# - badges: true
# - comments: true
# - author: Isaac Kargar
# - categories: [machine learning, deep learning]
# - show_image: true
# - image: _notebooks/my_icons/alphago/alphago_0.png

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_0.png?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_1.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_2.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_3.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_4.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_5.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_6.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_7.jpeg?raw=1)

# ![](https://github.com/kargarisaac/blog/blob/master/_notebooks/my_icons/alphago/alphago_8.jpeg?raw=1)

# That’s it for the first one. In the next post, I will review the AlphaGo Zero paper.