Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code by John T. Wolohan (Early release, v.6)
Requirements: .ePUB, .PDF reader, 5 mb, 8 mb
Overview: Mastering Large Datasets with Python teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data.
Genre: Non-Fiction > Tech & Devices
With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You’ll get familiar with Python’s functional built-ins like the functools operator and itertools modules, as well as the toolz library.
You’ll also dive into parallel processing using the standard multiprocessing module, the third-party pathos framework, Apache Hadoop, Apache Spark, and PySpark. You’ll even learn how to use these tools on a cloud platform like AWS. The many hands-on exercises throughout ensure your new knowledge sticks. By the end of this comprehensive guide, you’ll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level!
Download Instructions:
ePUB:
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PDF:
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Code (5 mb):
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