The purpose of this project is to introduce a shortcut to developers and researcher for finding useful resources about TensorFlow.


There are different motivations for this open source project.

Why using TensorFlow?

A deep learning is of great interest these days, the crucial necessity for rapid and optimized implementation of the algorithms and designing architectures is the software environment. TensorFlow is designed to facilitate this goal. The strong advantage of TensorFlow is it flexibility is designing highly modular model which also can be a disadvantage too for beginners since lots of the pieces must be considered together for creating the model. This issue has been facilitated as well by developing high-level APIs such as Keras and Slim which gather lots of the design puzzle pieces. The interesting point about TensorFlow is that its trace can be found anywhere these days. Lots of the researchers and developers are using it and its community is growing with the speed of light! So the possible issues can be overcame easily since they might be the issues of lots of other people considering a large number of people involved in TensorFlow community.

What’s the point of this open source project?

There other similar repositories similar to this repository and are very comprehensive and useful and to be honest they made me ponder if there is a necessity for this repository! A great example is awesome-tensorflow repository which is a curated list of different TensorFlow resources.

The point of this repository is that the resources are being targeted. The organization of the resources is such that the user can easily find the things he/she is looking for. We divided the resources to a large number of categories that in the beginning one may have a headache!!! However, if someone knows what is being located, it is very easy to find the most related resources. Even if someone doesn’t know what to look for, in the beginning, the general resources have been provided.

How to make the most of this effort

The written and visual resources have been split. Moreover, As one can search in the documentation, the number of categories might look to be too much. For finding the most relevant resources, please at first look through the general resources.