Wish Pearl

Parallel Python with Dask: Perform distributed computing, concurrent

Description: 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 on DaskML and deep learning showcase how to build scalable models with PyTorch and TensorFlow. With this book, you'll gain practical skills to: Accelerate Python workloads with parallel mapping and task schedulingSpeed up NumPy, Pandas, Scikit-Learn, PyTorch, and other librariesBuild scalable machine learning pipelines for large datasetsLeverage GPUs efficiently via Dask, RAPIDS and JAXManage Dask clusters and workflows for distributed computingStreamline deep learning models with DaskML and DL frameworks Packed with hands-on examples and expert insights, this book provides the complete toolkit to harness Dask's capabilities. It will empower Python programmers, data scientists, and machine learning engineers to achieve faster workflows and operationalize parallel computing. Table of ContentIntroduction to DaskDask FundamentalsBatch Data Parallel Processing with DaskDistributed Systems and DaskAdvanced Dask: APIs and Building BlocksDask with PandasDask with Scikit-learnDask and PyTorchDask with GPUsScaling Machine Learning Projects with Dask

Price: 104 AUD

Location: Hillsdale, NSW

End Time: 2024-11-05T04:17:53.000Z

Shipping Cost: 33.17 AUD

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Parallel Python with Dask: Perform distributed computing, concurrentParallel Python with Dask: Perform distributed computing, concurrent

Item Specifics

Return shipping will be paid by: Buyer

Returns Accepted: Returns Accepted

Item must be returned within: 60 Days

Return policy details:

EAN: 9788119177653

UPC: 9788119177653

ISBN: 9788119177653

MPN: N/A

Format: Paperback, 174 pages

Author: Peters, Tim

Book Title: Parallel Python with Dask: Perform distributed com

Item Height: 0.9 cm

Item Length: 23.5 cm

Item Weight: 0.31 kg

Item Width: 19.1 cm

Language: Eng

Publisher: Gitforgits

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