“Life is really simple, but we insist on making it complicated” ~ Confucius

Simple is harder than complex. And this's particularly true of academic research and ML models. I'm always on the lookout for resources that aim to simply describe statistical concepts and machine learning in an simple manner. Those who can do so truly understand the topic.

Here's an ongoign list of blogs and resources that I love the most.

Resources

• Chris Said's Blog: Some amazing posts on inferential statistics.
• Andrej Karpathy Blog: Incredible posts on neural networks. I'd recommend start with his description of Recurrent Neural Networks here
• MIT Course on Deep Learning Excellent resource with academic lectures.
• Lex Friedman's Blog Post: Covers the different architectures of Neural Networks. This is a must read!