Key Features
Discover techniques to build, monitor, and optimize your data science projectsMove from prototyping to production using Comet and DevOps toolsGet to grips with the Comet experimentation platform
Book Description
This book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model.
The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You'll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available.
By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet.
What you will learn
Prepare for your project with the right dataUnderstand the purposes of different machine learning algorithmsGet up and running with Comet to manage and monitor your pipelinesUnderstand how Comet works and how to get the most out of itSee how you can use Comet for machine learningDiscover how to integrate Comet with GitLabWork with Comet for NLP, deep learning, and time series analysis
Who this book is for
This book is for anyone who has programming experience, and wants to learn how to manage and optimize a complete data science lifecycle using Comet and other DevOps platforms. Although an understanding of basic data science concepts and programming concepts is needed, no prior knowledge of Comet and DevOps is required.
Table of Contents
An Overview of CometExploratory Data Analysis in CometModel Evaluation in CometWorkspaces, Projects, Experiments and ModelsBuilding a Narrative in CometIntegrating Comet into DevOpsExtending the Gitlab DevOps Platform with CometComet for Machine LearningComet for Natural Language ProcessingComet for Deep LearningComet for Time Series Analysis