Occasionally, I take notes on Machine Learning and toss them on here. If you’re looking to get started with ML, maybe you’ll find them useful. Pour yourself a cup of something warm, and follow along on the journey!
Wherever possible, I’ll share original data and code and invite you the reader to explore the data on your own, find your own insights and tell your own stories! This space will be updated occasionally with a list of interesting projects so you don’t have to wade through my Kaggle.
In Part I, Best Practices for Picking a Machine Learning Model, we talked about the part art, part science ofContinue Reading
Training neural networks can be very confusing! What’s a good learning rate? How many hidden layers should your network have?Continue Reading
Getting started with competitive data science can be quite intimidating. But it’s actually surprisingly simple! I recently started messing aroundContinue Reading
The Goal What’re we doing? We’re going to let XGBoost, LightGBM and Catboost battle it out in 3 rounds: Classification:Continue Reading
Getting started with Kaggle can be an intimidating prospect! So I wrote a kernel to help you get started quickly.Continue Reading