WandB — The Best MLOps Platform

Getting Started with Weight & Biases: A Mini Project Overview.

Building and deploying machine learning models requires a full lifecycle, and MLOps help manage this lifecycle by providing a set of best practices, tools, and frameworks that enable teams to develop, test, deploy, and monitor machine learning models in a scalable and reliable manner.

An MLOps lifecycle includes processes for data preparation and management, model training and validation, model deployment and monitoring, and ongoing model maintenance and improvement. A few months ago I wrote an article about MLFlow, a framework that provides many of the tools needed to build effective lifecycle steps.

Weight & Biases is a platform for tracking and visualising machine learning experiments. It is a great tool for MLOps. It provides a dashboard to visualise the metrics and the parameters of the experiments. It also provides a model registry that allows to deploy a model in a production environment with a single command.

In an article in 2018, the founder of W&B, Lukas Biewald, recalls his first experience with machine learning in 2002 when he trained his first algorithm to play Othello against itself. At the time, access to training data was the biggest problem in machine learning, and Biewald quit his job to…