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The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. This repository is dedicated to suggesting a simple path to learn TensorFlow. In addition to the aforementioned points, the large community of TensorFlow enriches the developers with the answer to almost all the questions one may encounter. Furthermore, since most of the developers are using TensorFlow for code development, having hands-on on TensorFlow is a necessity these days. Tensorboard is a powerful visualization suite that is developed to track both the network topology and performance, making debugging even simpler.
Features
- It’s developed and maintained by Google. As such, a continued support and development is ensured
- Low-level and high-level interfaces to network training
- Multiple GPUs support. So you can freely run the code on different machines without having to stop or restart the program
- Faster model compilation than Theano-based options
- Faster compile times than Theano
- TensorFlow actually has tools to support reinforcement learning and other algorithms
Project Samples
