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Parallel Python with Dask: Perform distributed computing, concurrent programming and manage large dataset by Tim Peters is a nonfiction available to read on EtoBox.

What is Parallel Python with Dask: Perform distributed computing, concurrent programming and manage large dataset about?

Unlock the Power of Parallel Python with Dask: A Perfect Learning Guide for Aspiring Data Scientists Dask has revolutionized parallel computing for Python, empowering data scientists to accelerate their workflows. This comprehensive guide unravels the intricacies of Dask to help you harness its capabilities for machine learning and data analysis. Across 10 chapters, you'll master Dask's fundamentals, architecture, and integration with Python's scientific computing ecosystem.Step-by-step tutorials demonstrate parallel mapping, task scheduling, and leveraging Dask arrays for NumPy workloads.You'll discover how Dask seamlessly scales Pandas, Scikit-Learn, PyTorch, and other libraries for large datasets. Dedicated chapters explore scaling regression, classification, hyperparameter tuning, feature engineering, and more with clear examples. You'll also learn to tap into the power of GPUs with Dask, RAPIDS, and Google JAX for orders of magnitude speedups. This book places special emphasis on practical use cases related to scalability and distributed computing. You'll learn Dask patterns for cluster computing, managing resources efficiently, and robust data pipelines. The advanced chapters

Who reads Parallel Python with Dask: Perform distributed computing, concurrent programming and manage large dataset?

Author

Tim Peters

Publisher

Gitforgits

Published

2023

Language

EN

Category

nonfiction

Subjects

Computer Science, Programming, Stem