Reproducing research papers is a rewarding way to boost your machine learning skills. But the practice can be deceptively complicated. If you’re thinking about giving it a try, Matthew Rahtz shares some hard-won insights from his first go at reproducing a Deep Reinforcement Learning paper.
Excited about new ML-based tools for musicians? Check out this WaveGAN code by Chris Donahue, Julian McAuley, and Miller Puckette. It’s a GAN approach designed for use on audio samples; try their groovy in-browser drum sampler demo.
Read on for more of the month's data science notes, highlights and competitions.