Pemrograman Paralel dengan Dask di Python

This chapter will teach you the basics of Dask and lazy evaluation. At the end of this chapter, you'll be able to speed up almost any Python code by using parallel processing or multi-threading. You'll learn the difference between these two task scheduling methods and which one is better under which circumstances.

Here you’ll learn how to analyze big structured data using Dask arrays and Dask DataFrames. You'll learn how everything you know about NumPy and pandas can easily be applied to data that is too large to fit in memory.

Process any kind of data. You'll learn how Dask bags can be used to efficiently process unstructured text data, semi-structured JSON data, and even recorded audio.

Harness the power of Dask to train machine learning models. You'll learn how to train machine learning models on big data using the Dask-ML package, and how to split Dask calculations across a mixture of processes and threads for even greater computing speed.