Brookhaven AIMS Tutorial: Numpy and tabular data

US/Eastern
Description

In 2023, we have expanded the Brookhaven AIMS series to include also hands-on tutorials organized by the BNL Computational Science Initiative, which are aimed at researchers, educators and students new to machine learning and artificial intelligence. The tutorial presentations are designed for a general audience, and minimal prior experience will be required.

 

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      Numpy and tabular data

      Abstract: Essentially all of data-driven science uses tabular data, which can best be thought of as collections of individual data points that all share the same features. For example, a parking garage may contain many different cars, and each car can share the same set of features: number of seats, purchase year, etc. Manipulating tabular data is a key skill for any AI or machine learning application. In this tutorial, you will learn the fundamentals of NumPy (the canonical numerical scientific computing package in Python), and how to use it to its utmost efficiency.

      GitHub link: https://github.com/matthewcarbone/AIML-tutorials

      Speaker: Matthew Carbone (Brookhaven National Laboratory)