TensorFlow is arugably the most popular deep learning library as of 2017.
This is designed to help those who want to familiarize themselves with TensorFlow functions. Particulary, I focus on comparing TensorFlow functions with the equivalent functions in NumPy, the de facto standard numerical computation library. I hope this will help you get comfortable with TensorFlow quickly.
The basic outline will be as follows, though this is not 100% fixed.
- Constants, Sequences, and Random Values (DONE)
- Graphs (DONE)
- Variables (DONE)
- Reading Data (DONE)
- Tensor Transformations (DONE)
- Math Part 1 (DONE)
- Math Part 2 (DONE)
- Math Part 3 (DONE)
- Strings (WIP)
- Control Flow (DONE)
- Images (WIP)
- Sparse Tensors (DONE)
- Neural Network Part 1 (DONE)
- Neural Network Part 2 (DONE)
- Neural Network Part 3 (WIP)
- Seq2Seq (DONE)
- Audio_Processing (DONE)
Enjoy!