10 Must Read ML Blog Posts

A collection of high-impact machine learning blog posts.

I have been doing NLP/ML research for the last 6 years. I have come across a lot of machine learning resources and papers. Today, I kept thinking about the machine learning / NLP / deep learning related blog posts (not papers) that have been transformational for me. In this blog post, I provide a short collection of a few high-impact blog posts that come to mind.

This post was originally a Twitter thread.


1) The Unreasonable Effectiveness of Recurrent Neural Networks

by Andrej Karpathy

🔗 link

2) Understanding Convolutional Neural Networks for NLP

by Denny Britz

🔗 link

3) Language Models

by Vered Shwartz

🔗 link

4) An overview of gradient descent optimization algorithms

by Sebastian Ruder

🔗 link

5) Understanding LSTM Networks

by Chris Olah

🔗 link

6) Deep Learning: Our Miraculous Year 1990-1991

by Jürgen Schmidhuber

🔗 link

7) An Overview of Deep Learning for Curious People

by Lilian Weng

🔗 link

8) Attention and Memory in Deep Learning and NLP

by Denny Britz

🔗 link

9) Neural Networks and Deep Learning

by Michael Nielsen

🔗 link

10) Troubling Trends in Machine Learning Scholarship

by Zachary Lipton

🔗 link

Bonus….

11) The Illustrated Transformer

by Jay Alammar

🔗 link

The list will be different for every generation but these are some of the blog posts that had been transformational for me. There are many more high-quality blog posts out there, so feel free to share in the comments. I thank these and many other people for making ML more accessible and welcoming.