Work with Deep Learning Libraries

This is my work on exploring and working with Deep Learning libraries. For now, the work is on PyTorch.

Why this?

Well, there have been times where I've had ideas but didn't know how to implement things from scatch. I do a lot of code reading, but learning something extensively from a book is always better, I believe. This is for me, and for those who are interested in learning PyTorch. I'm looking forward to complete the book (link below)!

Book: https://www.packtpub.com/big-data-and-business-intelligence/deep-learning-pytorch

Daily Goals -

1. Started from December 16th 2018. Learnt Basics, Tensors. Completed till Chapter 2
2. Updates(20th December '18) - Now on Chapter 3, (December 20 '18). Goal to complete Chapter 4, (by December 21 '18).
3. Updates(21st December '18) - Now on Chapter 5, completed Chapter 3 and Chapter 4. Goal to complete Chapter 5 today.
4. Updates(22nd December '18) - Completed Chapter 5. Goal to complete Chapter 6 by 23rd December '18.
5. Updates(23rd December '18) - I got lazy studying Chapter 6 - Deep Learning for NLP, too much of basics. Completed them though. Goal to complete Chapter 7 by 24th December
6. Updates(28th December '18) - Completed Book! <3

Projects

Now starting small projects to get hands on PyTorch.

1. Feed Forward NN: Completed Jan 15 2019
   • Reference: https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/feedforward_neural_network
2. Transfer Learning using FastAI and PyTorch (both). Completed March 12 2019
3. Face Recognition (Under Progress)
4. Linear Regression (Using PyTorch vs Scikit-Learn)