Resources for teaching machine learning and deep learning
W&B is a great tool for learning and collaboration. We offer free academic accounts, and we've collected some good resources for helping you and your students navigate complex machine learning projects.
Request an academic team to get started having your students submit results to a shared workspace. Grading projects is easy when you can see the real, tracked results and the code that students used to generate models.
Ask your students to submit reports so you can explore their results and compare new projects against previous baselines. Reports make it easy to describe intermediate results and show progress, and all the graphs are connected to real model results that you can reproduce. View an example report →
Create a project in your academic team, and have your students compete to achieve the best accuracy on a shared task. Here's a screenshot of an example competition. Each row is a different experiment, and users are competing for the highest accuracy. View the project →
Example script repo
We've built up a set of working examples of deep learning projects in different frameworks.