https://github.com/Kyubyong/tensorflow-exercises

TensorFlow Exercises - focusing on the comparison with NumPy.
https://github.com/Kyubyong/tensorflow-exercises

numpy tensorflow tensorflow-exercises

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TensorFlow Exercises - focusing on the comparison with NumPy.

• Host: GitHub
• URL: https://github.com/Kyubyong/tensorflow-exercises
• Owner: Kyubyong
• License: other
• Created: 2016-11-17T02:07:52.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2019-06-06T06:40:58.000Z (over 5 years ago)
• Last Synced: 2024-11-10T11:07:17.519Z (about 1 month ago)
• Topics: numpy, tensorflow, tensorflow-exercises
• Language: Python
• Homepage:
• Size: 1.89 MB
• Stars: 536
• Watchers: 26
• Forks: 170
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# TensorFlow Exercises

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!