AIM Banners_978 x 90

A Guide to Dask: Parallel Computing Tool in Python for Big Data

Parallel computing is a sort of computation that performs several calculations or processes at the same time.
When you open a large Dataset with Python's Pandas and try to get a few metrics, the entire thing just stops badly. If you work with Big Data on a regular basis, you're probably aware that if you're using Pandas, a simple loading of a series for a couple of million rows can take up to a minute! In the industry, the term/technique parallel computing is used for this. In relation to parallel computing, we will cover parallel computing and the Dask library, which is preferred for such tasks in this article. We will also go through different machine learning features as well available with Dask. The following are the main points to be discussed. Table of Contents What is Parallel Computing?Need of DaskWhat is Dask?Implementing DaskDask DataFrameDask ML Let’s start by understanding p
Subscribe or log in to Continue Reading

Uncompromising innovation. Timeless influence. Your support powers the future of independent tech journalism.

Already have an account? Sign In.

📣 Want to advertise in AIM? Book here

Picture of Vijaysinh Lendave
Vijaysinh Lendave
Vijaysinh is an enthusiast in machine learning and deep learning. He is skilled in ML algorithms, data manipulation, handling and visualization, model building.
Related Posts
AIM Print and TV
Don’t Miss the Next Big Shift in AI.
Get one year subscription for ₹5999
Download the easiest way to
stay informed