- 【TensorFlow 资料】The Ultimate List of TensorFlow Resources: Books, Tutorials, Libraries and More
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.
2.【课程】Applied Deep Learning
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。
3.【论文&代码】Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
This implementation contains:
- Deep Q-network and Q-learning
- Experience replay memory
to reduce the correlations between consecutive updates
- Network for Q-learning targets are fixed for intervals
to reduce the correlations between target and predicted Q-values
4.【博客&论文】Neural Network Architectures
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.
5.【Tutorial】ACL 2016 Tutorial: Understanding Short Texts
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.