Mastering Large Datasets with Python

▪️About the book:
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.

▪️What's inside:
• An introduction to the map and reduce paradigm
• Parallelization with the multiprocessing module and pathos framework
• Hadoop and Spark for distributed computing
• Running AWS jobs to process large datasets

▪️About the reader:
For Python programmers who need to work faster with more data.


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