Comet Office Hours Working Session #1: Project Setup

Through this project, they will illustrate the importance and value of creating a standardized workflow for your projects.

In this first working session, Dhruv and Michael outline their approach to the project, including its definition and scope, their Git repo structure, the project's source code, and more.

00:00 Project Introduction
09:28 Explaining the Source Code
16:01 Organizing Experiments in Comet
17:28 Visualizing Experiment Results with Comet Panels
18:34 Discussing the Dataset and the Nature of the Problem

Additional Sessions:

**Working Session #6: Feature Engineering Experiment Explanation:
**Working Session #7: Using the Comet Optimizer:
**Working Session #8: Regression Model Intro:
**Working Session #9: Building a Regression Model and Hyperparameter Search:

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About Comet Office Hours:

Seven Simple Steps to a More Standardized Machine Learning Process

Description

This virtual series will take place over eight weeks with expert panelists, lectures from our host Harpreet Sahota, community practitioner interviews, and more. Series 1 will cover:

* Defining Business Impact with Your Machine Learning Projects
* How to Define Scope and Success Criteria for Your Machine Learning Projects
* Understanding, Validating, Versioning, and Engineering your Data
* How to Manage Experiments Like an Expert
*And more

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About Comet:

Comet provides a self-hosted and cloud-based meta machine learning platform allowing data scientists and teams to track, compare, explain and optimize experiments and models.

Backed by thousands of users and multiple Fortune 100 companies, Comet provides insights and data to build better, more accurate AI models while improving productivity, collaboration and visibility across teams.