Join us for an exciting virtual workshop where you'll learn from Thomas Capelle, a top machine learning engineer at Weights and Biases, who works on the Growth Team. In this workshop, you'll get hands-on experience with Weights and Biases and learn how to take your machine-learning experiments to the next level.
Thomas will lead a walkthrough where you'll learn how to use Weights and Biases to track and visualize your experiments, debug your models, and make better decisions. He'll also share his expertise on ML-Ops, the applications of W&B to the industry, and fun deep learning.
After the walkthrough, we'll have an interactive competition where you can put your skills to the test and win unique Weights & Biases swag (shipped directly to you)! 🎉🎉🎉
Whether you're a seasoned machine learning practitioner or just starting out, this workshop is perfect for anyone looking to improve their skills and make ML more fun and reproducible with Weights and Biases. So don't miss out on this opportunity to learn from one of the top machine learning engineers in the industry and connect with like-minded individuals!
Weights & Biases is free for personal use and academic projects and easy to start. You do not need to install anything on your laptop, as you will be provided with Google Colab notebooks. Everything else will be explained at the event!
To learn more about Weights & Biases you can check out their website!
Weights & BIases
Machine Learning Engineer
Thomas Capelle is a Machine Learning Engineer at Weights and Biases who works on the Growth Team. With a background in Urban Planning, Combinatorial Optimization, Transportation Economics, and Applied Math, Thomas brings a wealth of knowledge and experience to the table.
At Weights and Biases, Thomas is responsible for keeping the wandb/examples repository live and up to date. He also bu…
Thomas Capelle is a Machine Learning Engineer at Weights and Biases who works on the Growth Team. With a background in Urban Planning, Combinatorial Optimization, Transportation Economics, and Applied Math, Thomas brings a wealth of knowledge and experience to the table.
At Weights and Biases, Thomas is responsible for keeping the wandb/examples repository live and up to date. He also builds content on ML-OPS, application of wandb to industry, and many other deep learning projects. Prior to his work at Weights and Biases, he was using deep learning to solve short-term forecasting for solar energy at Steady Sun.
As a top machine learning engineer, Thomas is passionate about helping others improve their skills with Weights and Biases. He is dedicated to making complex topics more accessible and is always happy to answer questions and share his expertise.
GDSC Munich Lead
GDSC Munich Lead
GDSC Munich Core Team
GDSC Munich Core Team
GDSC Munich Advisor
GDSC Munich Advisor
GDSC Munich Core Team
GDSC Munich Core Team
Technical University of Munich
GDSC Munich Core Member
GDSC Munich Core Member
TUM
GDSC Munich Core Team
GDSC Munich Core Team
