Scaling Python with Dask- From Data Science to Machine Learning (Early Release, Raw and Unedited) PDF
Preview Scaling Python with Dask- From Data Science to Machine Learning (Early Release, Raw and Unedited)
Dask is a free and open source library for parallel computing in Python that helps you scale your data science and machine learning workflows. With this quick but thorough resource, data scientists and Python programmers will learn how Dask provides APIs that make it easy to parallelize PyData libraries like NumPy, pandas, and scikit-learn.
Author Holden Karau shows you how you can use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA.
With this book, you'll learn about
What is Dask is, where you can use it, and how it compares to other tools
Batch data parallel processing
Key distributed system concepts for Dask users
Higher-level APIs and building blocks
Integrated libraries, such as scikit-learn, pandas, and PyTorch
How to use Dask with GPUs
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