Skip to main content
HomeCode-alongsMachine Learning

Introduction to Experiment Tracking

This webinar shows you how to get started with experiment tracking, a pivotal yet frequently overlooked aspect of the data science lifecycle.
Jul 2023

It is very common for organizations to run many experiments - such as A/B tests - at the same time. The knowledge gained from these tests can only be acted upon if they are carefully managed and studied. This webinar shows you how to get started with experiment tracking, a pivotal yet frequently overlooked aspect of the data science lifecycle. You'll learn about the importance experiment tracking plays in ensuring reproducibility and how using it can allow you to update your internal understanding of your task more systematically. You'll also discover how to use DagsHub to manage a single data experiment, then how to scale this to many experiments.

Key Takeaways:

  • Learn the steps involved in tracking data experiments.
  • Learn how to scale your use of experiments.
  • Learn how to use DagsHub for managing experiments and other machine learning projects.
Additional Resources
 
We use DagsHub in this webinar, sign up for an account here.
 
Topics
Related

tutorial

Streamline Your Machine Learning Workflow with MLFlow

Take a deep dive into what MLflow is and how you can leverage this open-source platform for tracking and deploying your machine learning experiments.
Moez Ali 's photo

Moez Ali

12 min

code-along

Running Machine Learning Experiments in Python

In this webinar, you'll use MLflow to manage a machine learning experiment pipeline. The session will cover model evaluation, hyperparameter tuning, and MLOps strategies, using a London weather dataset.
Folkert Stijnman's photo

Folkert Stijnman

code-along

Getting Started with Machine Learning in Python

Learn the fundamentals of supervised learning by using scikit-learn.
George Boorman's photo

George Boorman

code-along

Data Storytelling for Absolute Beginners: A Case Study with Green Businesses

In this webinar for data novices, you'll learn about several ways in which you can visualize your data, understand how plots work and structure a story around them.
Camilo Martinez's photo

Camilo Martinez

code-along

Only Code If You Want To: Data Science with DataLab (Part 1)

Find out how to use DataLab's chat interface to perform data analysis using a completely conversational workflow.
Filip Schouwenaars's photo

Filip Schouwenaars

code-along

Exploratory Data Analysis in Python for Absolute Beginners

In this live codealong, you will learn the basics of exploring new datasets
Filip Schouwenaars's photo

Filip Schouwenaars

See MoreSee More