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!