Abstract: According to a recent survey, about 50% of Data Science projects were abandoned before moving
to production. This was essentially due to the lack of the right platform for managing the project life
cycle. In this tutorial, we'll introduce you to model tracking platforms - software that can help you
boost your productivity by keeping track of your progress and goals.
A model tracking platform is a web-based tool that can be used to manage multiple models, track
changes over time, and see which versions are most successful. Using a model tracking platform
can help you optimize your workflows and make better use of your time.
Using a model tracking platform can help you stay organized and improve your productivity. It is a
valuable tool for both individual users and teams who are working on machine learning projects. By
keeping track of your models and projects in one place, you can save time and stay organized. A
model tracking platform can also help you collaborate with team members, clients, and vendors.
When it comes to model tracking platforms, there are a lot of options out there. In this tutorial, we’ll
use Comet, a platform for model tracking and monitoring.
Session Outline:
In detail, you’ll learn how to:
1. get started with Comet
2. keep track of all your models in one place.
2. see how each model is performing and identify areas for improvement.
3. share models with other users and get feedback.
4. choose the best model for production.
Background Knowledge:
Very familiar with Python
Bio: Angelica Lo Duca is a researcher at the Institute of Informatics and Telematics of the National Research Council, Italy. She is also an external professor of Data Journalism at the University of Pisa. Her research interests include Data Science, Data Journalism, and Web Applications. She used to work on Network Security, Semantic Web, Linked Data, and Blockchain. She has published more than 40 scientific papers at national and international conferences and journals. She has participated in different national and international projects, and events. She has been a member of the Program Committee at different conferences. She is also the author of the book Comet for Data Science, published by Packt Ltd.
