Mastering large datasets with Python

• Titel: Mastering large datasets with Python
• Mitwirkende: Wolohan, John [VerfasserIn]
• Institutionen: Manning Publications, [Verlag]
• Verf.angabe: John Wolohan
• Ausgabe: [First edition].
• Verlagsort: [Shelter Island, New York]
• Verlag: Manning Publications
• E-Jahr: 2020
• Jahr: [2020]
• Umfang: 1 online resource (1 video file (7 hr., 45 min.))
• Illustrationen: sound, color.
• Fussnoten: "In video editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.". - Online resource; title from title details screen (O'Reilly, viewed December 2, 2024)
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Python (Langage de programmation)
• Form-SW: Instructional films
• Form-SW: Nonfiction films
• Form-SW: Internet videos
• Form-SW: Films de formation
• Form-SW: Films autres que de fiction
• Form-SW: Vidéos sur Internet
• K10plus-PPN: 1914062191
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4648244982
• Lokale URL Inst.: Zum Volltext

Abstract

Mastering Large Datasets with Python teaches you to write code that can handle datasets of any size. You'll start with laptop-sized datasets that teach you to parallelize data analysis by breaking large tasks into smaller ones that can run simultaneously. You'll then scale those same programs to industrial-sized datasets on a cluster of cloud servers. With the map and reduce paradigm firmly in place, you'll explore tools like Hadoop and PySpark to efficiently process massive distributed datasets, speed up decision-making with machine learning, and simplify your data storage with AWS S3.