How to Track Progress and Collaborate in Data Science and Machine Learning Projects

Discover practical guidelines and tips for setting up and maintaining smooth collaboration in data science projects in this 31-minute conference talk from MLCon | Machine Learning Conference. Learn how to organize work around creative iterations, making it reproducible and easily shareable. Explore techniques for tracking code, metrics, hyperparameters, learning curves, and data versions. Address mutual communication needs between data scientists and business people. Presented by Jakub Czakon and Kamil Kaczmarek from neptune.ml, this talk provides valuable insights into effective project management and collaboration in the field of data science and machine learning.

How to track progress and collaborate in data science and machine learning projects?