About one year ago, I have discovered Comet, an experimentation platform for model tracking and monitoring. Since then, I have used Comet’s features to keep my projects organized and make them move from the early stages to production. The simplicity of Comet’s platform helped me complete all of the projects on it.
While studying Comet, I came across Heartbeat, a Medium publication edited by the Comet team, and started writing for them. Thanks to Heartbeat, I deepened several aspects of Comet, and I moved from the simple role of data analyst to that of a builder.
I authored Comet for Data Science as the result of my studies and tests, after talking with the Comet team and performing my personal tests.
Throughout the book, you will learn how to build a successful Data Science project, starting from the first steps, up to model deployment. In detail, the book will take you through the concepts of Data Science from a Comet perspective, with the hope that it will increase your productivity. By choosing this book, you will learn about data science from Comet’s point of view, with the hope that you will be able to increase your speed in creating these projects. Throughout the course of the book, you will see many practical examples that are used to better understand the concepts, and can also serve as starting points for your own projects.
The book is organized as follows:
Getting Started with Comet
- An Overview of Comet
- Exploratory Data Analysis in Comet
- Model Evaluation in Comet
A Deep Dive to Comet
- Workspaces, Projects, Experiments and Models
- How to Build a Narrative in Comet
- An Overview of DevOps concepts
- Extending the Gitlab DevOps platform with Comet
Examples and Use Cases
- Comet for Machine Learning
- Comet for Natural Language Processing
- Comet for Deep Learning
- Comet for Time Series Analysis
- You can find more details about the book at https://www.cometfordatascience.com/
Happy reading!
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