Python and R for the Modern Data Scientist (Paperback)

Rick Scavetta

ISBN 10: 1492093408 / ISBN 13: 9781492093404

Edité par O'Reilly Media, Sebastopol, 2021

A propos de cet article

Paperback. Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. With this book, data scientists from the Python and R communities will learn how to speak the dialects of each language. By recognizing the strengths of working with both, you'll discover new ways to accomplish data science tasks and expand your skill set.Authors Boyan Angelov and Rick Scavetta explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. Not only will you learn how to use Python and R together in real-world settings, but you'll also broaden your knowledge and job opportunities by working as a bilingual data scientist.Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a real-world case study that demonstrates ways to use these languages together" With this book, data scientists from the Python and R communities will learn how to speak the dialects of each language. By recognizing the strengths of working with both, you'll discover new ways to accomplish data science tasks and expand your skill set. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

N° de réf. du vendeur 9781492093404

Détails bibliographiques

• Titre: Python and R for the Modern Data Scientist (Paperback)
• Éditeur: O'Reilly Media, Sebastopol
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 1492093408
• ISBN à 13 chiffres: 9781492093404
• Reliure: Paperback
• État de l'article: new

A propos de ce titre

Synopsis

Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set.

Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist.

• Learn Python and R from the perspective of your current language
• Understand the strengths and weaknesses of each language
• Identify use cases where one language is better suited than the other
• Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows
• Learn how to integrate R and Python in a single workflow
• Follow a case study that demonstrates ways to use these languages together

À propos des auteurs

Rick Scavetta has worked as an independent workshop trainer, freelance data scientist and co-founder since 2012. Operating as Scavetta Academy, Rick has a close and recurring presence at primary research institutes across Germany. His online courses at DataCamp have been taken by over 200,000 students since 2016 and he's also contributed to advanced data science courses for O'Reilly and Manning. Rick currently serves as the technical curriculum advisor to the Misk Academy in Saudi Arabia and heads the development of their Data Science programme.

Boyan Angelov is a Senior Data Scientist, Engineering Manager, and Consultant with almost a decade of experience in a variety of academic and industry environments, covering a variety of topics such as bioinformatics, clinical trials, HRTech, and management consulting. He is additionally a contributor to open source scientific projects in the field of xAI, and speaks regularly at conferences and meetups.