Machine Learning - Page 4

← Back to All Tags

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.

Enjoy!

Machine Learning Meme Collection

April Fools

An increasingly necessary component of being engaged on ML Twitter

Read

How to approach algorithm problems

Programming

An example that's probably closer to what you're experiencing in coding interviews

Read

Using TPUs in Google Colab (properly)

Machine Learning

A simple way to use TPUs with minimal hardware optimization

Read

A quick intro to Bayesian neural networks

Machine Learning

Making neural networks shrug their shoulders

Read

An introduction to probabilistic programming, now available in TensorFlow Probability

Machine Learning

Announcement for the work I did with the TFP Team at Google

Read

Getting started with Attention for Classification

Tutorials

A quick guide on how to start using Attention in your NLP models

Read

An introduction to probabilistic programming, now available in TensorFlow Probability

Machine Learning

Guest Post by Michael Shwe

Announcement for the work I did with the TFP Team at Google

Read