人工智能资料库:第10辑(20170116)

本文精选了50多个TensorFlow优质资源,包括书籍、教程、库和项目等。涵盖国立台湾大学深度学习课程、《通过深度强化学习实现人类级别控制》论文及其实现、神经网络架构回顾等内容。

  1. 【TensorFlow 资料】The Ultimate List of TensorFlow Resources: Books, Tutorials, Libraries and More

简介:

A curated list of 50+ awesome TensorFlow resources including tutorials, books, libraries, projects and more.

If you know of any awesome TensorFlow resources that you think should be added to this list, please let me know in the comments section.

And be sure to check out our other awesome lists of the best computer vision resources and free machine learning books.

原文链接:https://hackerlists.com/tensorflow-resources/


2.【课程】Applied Deep Learning

简介:

这是一个国立台湾大学的深度学习课程,应用领域是自然语言处理,授课老师是YUN-NUNG (VIVIAN) CHEN。

原文链接:https://www.csie.ntu.edu.tw/~yvchen/f105-adl/index.html


3.【论文&代码】Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning

简介:

This implementation contains:

  1. Deep Q-network and Q-learning
  2. Experience replay memory
    to reduce the correlations between consecutive updates
  3. Network for Q-learning targets are fixed for intervals
    to reduce the correlations between target and predicted Q-values

原文链接:http://home.uchicago.edu/~arij/journalclub/papers/2015_Mnih_et_al.pdf

代码链接:https://github.com/devsisters/DQN-tensorflow


4.【博客&论文】Neural Network Architectures

简介:

Deep neural networks and Deep Learning are powerful and popular algorithms. And a lot of their success lays in the careful design of the neural network architecture.

I wanted to revisit the history of neural network design in the last few years and in the context of Deep Learning.

原文链接:https://culurciello.github.io/tech/2016/06/04/nets.html

论文链接:https://arxiv.org/pdf/1605.07678v2.pdf


5.【Tutorial】ACL 2016 Tutorial: Understanding Short Texts

简介:

Billions of short texts are produced every day, in the form of search queries, ad keywords, tags, tweets, messenger conversations, social network posts, etc. Unlike documents, short texts have some unique characteristics which make them difficult to handle.

First, short texts, especially search queries, do not always observe the syntax of a written language. This means traditional NLP techniques, such as syntactic parsing, do not always apply to short texts.

Second, short texts contain limited context. An analysis based on Bing’s search logs shows that more than 97% of queries contain 1 to 8 words, and over 63% of queries only contain 1 or 2 words.

原文链接:http://www.wangzhongyuan.com/tutorial/ACL2016/Understanding-Short-Texts/


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