I write about AI, Biotech, and a bunch of other topics. Subscribe to get new posts by email!
© Matthew McAteer 2022
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:
- Lessons from becoming a Machine Learning Engineer in 12 months, without a CS or Math degree
- How to approach algorithm problems
- An introduction to probabilistic programming, now available in TensorFlow Probability
Similar tags include Tensorflow, GANs, and Private Machine Learning.
Enjoy!
Nitpicking Machine Learning Technical Debt
Revisiting a resurging NeurIPS 2015 paper (and 25 best practices more relevant than that for 2020)
ReadBuilding a better Patent Classifier
Building a classifier to tell you whether your LIDAR patent will be approved
ReadStyle Transfer with Binarized Neural Networks
Co-Authored by Vinay Prabhu
Neural Style Transfer with binary 0s and 1s instead of floating points in your ImageNet model
ReadStructural Similarity in Neural Style Transfer
Co-Authored by Vinay Prabhu
Bringing back an ancient computer vision technique to effortlessly improve style transfer results
Read