Course curriculum

    1. Introducing W&B

    2. Instrumenting W&B in your code

    3. Exploring W&B workspace

    4. Comparing & analyzing experiments

    5. Using W&B beyond experiment tracking

    6. Testing your knowledge

    7. Logging your first run

    8. More resources for you

About this course

  • Free
  • 8 lessons
  • 15 minutes of video content

Your Goals

Sign up for this free Weights & Biases course to

  • Discover

    the essential features of Weights & Biases for experiment tracking, hyperparameter optimization, data visualization, and collaboration.

  • Enhance

    your machine learning productivity and rapidly iterate on experiments to achieve better results.

  • Learn

    how to integrate W&B with your Python training script.

Prerequisites

  • Intermediate Python experience

  • Understanding of basic machine learning concepts

Instructor

Scott Condron

Machine Learning Engineer

Scott Condron is a Machine Learning Engineer at W&B and works on the Growth team. He has a background in using Machine Learning for Speech and Audio applications and previously worked as a Research Engineer at Speech Graphics developing audio-driven facial animation tools.

Reviews

5 star rating

A superb, hands-on intro to W&B.

Aditya Tiwari

A well guided hands-on intro to W&B which gives a good idea of its experiment tracking capabilities.

A well guided hands-on intro to W&B which gives a good idea of its experiment tracking capabilities.

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5 star rating

Great first understanding of the product!

Immanuel Böker

I'm new to W&B and already learnt a lot about how useful this tool is.

I'm new to W&B and already learnt a lot about how useful this tool is.

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5 star rating

5 Stars

Muhammad Faizan

This is such a great course for understanding the system logs and monitoring and storing runs for each experiment. Highly recommended!

This is such a great course for understanding the system logs and monitoring and storing runs for each experiment. Highly recommended!

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