Exploration vs. Exploitation in Reinforcement Learning

We simulate a problem called the "multi-armed bandit" in order to understand the details of this tradeoff.

Using Dask in Machine Learning: Preprocessing Tutorial

We have used Dask extensively to build scalable ML pipelines. Here we cover the basics.

Custom Loss Functions for Gradient Boosting

We summarize the importance of custom loss functions in many real-world problems—and how to implement them with the LightGBM gradient boosting package.

Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-encoders

We introduce an auto-encoder architecture.

arXiv.org

Distance Matrix Vectorization Trick

A common problem that comes up in ML is needing to find the l2-distance between two sets of vectors.

Efficient Data Engineering

Reflecting on these well established tips in this context will help you approach data engineering problems with a fresh perspective.