【学习】最轻松的学习Tensorflow技术

最轻松的学习Tensorflow技术，Gentlest Intro to Tensorflow：

第1部分：使用Tensorflow进行单特征单一结果模型的线性回归

第2部分：用图表/代码来阐述的Tensorflow的训练机制，并探索训练的变化

第3部分：使用Tensorflow的矩阵和多特征线性回归

第4部分：使用Tensorflow的逻辑回归

Summary: Tensorflow (TF) is Google’s attempt to put the power of Deep Learning into the hands of developers around the world. It comes with a beginner & an advanced tutorial, as well as a course on Udacity. However, the materials attempt to introduce both ML and TF concurrently to solve a multi-feature problem — character recognition, which albeit interesting, unnecessarily convolutes understanding. In this series of articles, we present the gentlest introduction to TF that starts off by showing how to do linear regression for a single feature problem, and expand from there.

This is part of a series:

• Part 1 (this article): Linear regression with Tensorflow for single feature single outcome model

• Part 2: Tensorflow training illustrated in diagrams/code, and exploring training variations

• Part 3: Matrices and multi-feature linear regression with Tensorflow

• Part 4: Logistic regression with Tensorflow

链接：

https://medium.com/all-of-us-are-belong-to-machines/the-gentlest-introduction-to-tensorflow-248dc871a224#.htduxq9ij

原文链接：