Machine Learning - Page 2

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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.

Enjoy!

Thoughts on the GPT3 Decision

September 27, 2020Machine Learning

OpenAI's exclusive licensing of GPT-3 to Microsoft, and what this means for ML engineering

I'm on Datacast Episode 40

August 23, 2020Announcements

Hear me talk about machine learning, aging, drug discovery, and a bunch of other topics

Presenting at the ACAI 2020 Workshop

July 21, 2020Virtual AI Conferences

How to hold an AI conference in the COVID-19 era

Messing with GPT-3

July 16, 2020Machine Learning

Why OpenAI's GPT-3 doesn't do what you think it does, and what this all means

Nitpicking Machine Learning Technical Debt

May 10, 2020Paper Critiques

Revisiting a resurging NeurIPS 2015 paper (and 25 best practices more relevant than that for 2020)

Style Transfer with Binarized Neural Networks

July 25, 2020Neural Style Transfer

Co-Authored by Vinay Prabhu

Neural Style Transfer with binary 0s and 1s instead of floating points in your ImageNet model

Structural Similarity in Neural Style Transfer

July 24, 2020Neural Style Transfer

Co-Authored by Vinay Prabhu

Bringing back an ancient computer vision technique to effortlessly improve style transfer results