Tackling Big Data with MATLAB

Tackling Big Data with MATLAB

As your data sets grow in both size and complexity, it becomes more and more difficult to work with them, particularly when the data does not fit in memory. MATLAB provides a single, high-performance environment for working with big data that makes it easy, convenient, and scalable to analyze and process big data.

In this seminar, you will learn strategies and techniques for handling large amounts of data in MATLAB. New big data capabilities in MATLAB will be highlighted, including tall arrays. Using tall arrays, there's no need to learn big data programming or out-of-memory techniques -- simply use the same code and syntax you're already used to.

Lunch will be provided. Bring your laptop.

Topics covered include:

  • Accessing data in large text files, databases, or from the Hadoop Distributed File System (HDFS)
  • Leveraging tall arrays to analyze and process data that does not fit in memory
  • Using Parallel Computing Toolbox for increased performance
  • Running on compute clusters, Hadoop, or Spark

Presenter will be Reece Teramoto, an Application Engineer at MathWorks. He studied computer science and electrical engineering at the University of Portland. In 2017, he joined MathWorks and is currently a deep learning specialist supporting aerospace and defense accounts.

Tuesday, April 5, 2022
12:00pm - 2:00pm
Main B254/B252 Combined - Learning Studio CATalyst
Student Learning & Engagement
  UA faculty & instructors     UA graduate students     UA staff  
Registration has closed.