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Comet for data science : enhance your ability to manage and optimize the life cycle of your data science project /

Gain the key knowledge and skills required to manage data science projects using Comet Key Features Discover techniques to build, monitor, and optimize your data science projects Move from prototyping to production using Comet and DevOps tools Get to grips with the Comet experimentation platform Boo...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lo Duca, Angelica
Otros Autores: Mendels, Gideon
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited, 2022.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Lo Duca, Angelica. 
245 1 0 |a Comet for data science :  |b enhance your ability to manage and optimize the life cycle of your data science project /  |c Angelica Lo Duca. 
260 |a Birmingham :  |b Packt Publishing, Limited,  |c 2022. 
300 |a 1 online resource (402 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Print version record. 
504 |a Includes bibliographical references. 
520 |a Gain the key knowledge and skills required to manage data science projects using Comet Key Features Discover techniques to build, monitor, and optimize your data science projects Move from prototyping to production using Comet and DevOps tools Get 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 data Understand the purposes of different machine learning algorithms Get up and running with Comet to manage and monitor your pipelines Understand how Comet works and how to get the most out of it See how you can use Comet for machine learning Discover how to integrate Comet with GitLab Work 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. 
505 0 |a Table of Contents An Overview of Comet Exploratory Data Analysis in Comet Model Evaluation in Comet Workspaces, Projects, Experiments and Models Building a Narrative in Comet Integrating Comet into DevOps Extending the Gitlab DevOps Platform with Comet Comet for Machine Learning Comet for Natural Language Processing Comet for Deep Learning Comet for Time Series Analysis. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Application software  |x Development. 
650 0 |a Object-oriented programming (Computer science) 
650 0 |a Data mining. 
650 6 |a Logiciels d'application  |x Développement. 
650 6 |a Programmation orientée objet (Informatique) 
650 6 |a Exploration de données (Informatique) 
650 7 |a Application software  |x Development  |2 fast 
650 7 |a Data mining  |2 fast 
650 7 |a Object-oriented programming (Computer science)  |2 fast 
700 1 |a Mendels, Gideon. 
776 0 8 |i Print version:  |a Duca, Angelica Lo.  |t Comet for Data Science.  |d Birmingham : Packt Publishing, Limited, ©2022 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781801814430/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
938 |a Askews and Holts Library Services  |b ASKH  |n AH40273281 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL7072618 
938 |a EBSCOhost  |b EBSC  |n 3347000 
994 |a 92  |b IZTAP