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.
This open book is licensed under a MIT License. You can download TensorFlow Roadmap ebook for free in PDF format (0.3 MB).
Table of Contents
How to make the most of this effort
Entrance to TensorFlow World
Going Deeper in TensorFLow
Programming with TensorFlow
Reading data and input pipeline
Linear and Logistic Regression
Convolutional Neural Networks
Recurrent Neural Networks
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