Machine Learning - Page 3

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In a nutshell, Machine Learning is a way to give computers the powers of generalization. And that's what I try to do: put [seemingly complicated] things simply. My posts on Machine Learning (ML) focus mainly on recent cutting edge research, and how to make it accessible to everyone. I felt like many academic guides weren't accessible enough, so I strove to make my guides as clear and practically-focused as possible.

Unsure where to start? Here are some of my best / most popular posts:

Similar tags include Tensorflow, GANs, and Private Machine Learning.


Deploying and Scaling ML

Machine Learning

Practical considerations of scaling and implementing ML in the real world


Deep Learning Concepts every practicioner should know

Machine Learning

A deep dive into the important 'deep' learning concepts


Machine Learning Fundamentals

Machine Learning

Fundamentals of all types of machine learning, deep learning or otherwise


The Math Behind ML (the important stuff)

Machine Learning

Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other space


ML Research Interview Handbook


A 4-post series that covers the subject material in a good machine learning engineer interview.

View Series

Under-Investigated Fields List (Version 1.0)

Progress Studies

Nominations for fields that are not being researched as much as they should be


Avoiding Disaster in ML Projects

Project Management

A few high-level patterns to look out for in any projects you start or join