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Okładka: Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning

Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning

Autor: Ivan Marin, Ankit Shukla, Sarang VK

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Kategorie
Machine Learning, Pandas, Python w danych
Wydawca
Packt Publishing
Rodzaj
ebook
Stron
276
Data wydania
2019-04-10
ISBN
9781789950731
Tytuł oryginału
Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning
Formaty
PDF (5,0MB) · ePub (16,2MB) · Mobi (16,2MB)

Opis

Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems.

The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools.

By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs.

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