This article summarizes the high quality data of tensorflow, including documents, papers, books, courses and cases.
1 document
Getting Started With TensorFlow, start learning and understanding tensorflow from here.
Tensorflow programming personnel guide, guide how to use tensorflow programming.
Tensorflow tutorial, introduced tensorflow how to solve some classic problems. For example: image recognition, text mining and so on
2 papers
1 TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems, Google Corporation published tensorflow papers, the official version of the idea and use of tensorflow. (need paper, please add WeChat: luqin360)
3 books
1 Learning TensorFlow
This book provides an end to end guide to TensorFlow, and TensorFlow is the leading open source software library that helps you build and train neural networks for computer vision, Natural Language Processing (NLP), speech recognition and general predictive analysis. (need books, please add WeChat: luqin360)
4 course
1 Stanford University: Tensorflow for Deep Learning Research.
This course will cover the basic principles and usage of Tensorflow in depth learning research. The goal of the course is to help students understand the graphical computing models of Tensorflow, explore the functions they provide, and learn how to build models that are best suited for deep learning projects. Through this course, students will use Tensorflow to build different complexity models, from simple linear / logical regression to convolutional neural networks and recurrent neural networks with LSTM, to solve word embedding, translation, optical character recognition and other tasks.
5 case
Classic case of 1 tensorflow: https://github.com/aymericdamien/TensorFlow-Examples
Easy access to TensorFlow through cases. For ease of reading, it includes notebooks and source code and explanations. It is suitable for beginners who want to find clear and concise examples of TensorFlow. In addition to the traditional "primitive" TensorFlow implementation, you can also find the latest TensorFlow API practices (such as layers, estimators, data sets, and so on).
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