MATLAB seminars at University of Kentucky - September 16, 2015
Please join the Center for Computational Sciences and MathWorks for complimentary MATLAB seminars
on Wednesday, September 16, 2015 in the W.T. Young Library Room B108C.
This Workshop is free and open to the public
MATLAB Technical Seminars
Date: Wednesday, September 16, 2015
Times: 10:00 am – 12:00 p.m. , 1:00pm – 3:00 p.m. and 3:05pm - 4:05pm EST
Location: William T. Young Library Room #B108C University of Kentucky
(Walk-ins are Welcome)
Our event features a technical session presented by a MathWorks engineer:
10:00am - 12:00pm EST
Session One: Top 10 Productivity Tools in MATLAB
Registration and sign-in begins at 9:30 AM. Walk-ins are welcome.
In this technical session, we will present the unsanctioned but highly acclaimed list of “Top 10 Productivity Tools in MATLAB” – ways to increase your productivity and effectiveness as you use MATLAB to
* Explore, analyze, and visualize data,
* Develop, test, optimize, and maintain MATLAB algorithms and applications, and
* Consolidate and share results with colleagues
We will demonstrate key features and capabilities of the MATLAB Desktop Environment, including the MATLAB Editor, Command Window, Command History, Help Browser, Code Analyzer, Profiler, Plot Browser, and Plot Tools. The session is intended for scientists and engineers who have at least a basic working knowledge of the MATLAB Environment.
1:0pm - 3:00pm EST
Session Two: Data Analytics with MATLAB
Registration and sign-in begins at 12:30 PM. Walk-ins are welcome.
Using Data Analytics to turn large volumes of complex data into actionable information can help you improve design and decision-making processes. However, developing effective analytics and integrating them into business systems can be challenging. In this seminar you will learn approaches and techniques available in MATLAB® to tackle these challenges.
* Accessing, exploring, and analyzing data stored in files, the web, and data warehouses
* Techniques for cleaning, exploring, visualizing, and combining complex multivariate data sets
* Prototyping, testing, and refining predictive models using machine learning methods
* Integrating and running analytics within enterprise business systems and interactive web applications
3:05pm - 4:05pm EST
Session Three: Tackling Big Data with MATLAB
Registration and sign-in begins at 3:00 PM. Walk-ins are welcome.
Are the data sets you need to analyze becoming uncomfortably large to work with in memory? Are they taking too long to compute? Are you finding it challenging to scale your algorithms to big data sets? In this webinar, you will learn strategies and techniques for handling large amounts of data in MATLAB. New big data capabilities in MATLAB R2015a will be highlighted.
Topics covered include:
* Using best practices for memory use in MATLAB
* Accessing data in large text files, databases or from the Hadoop Distributed File System (HDFS)
* Leveraging distributed memory to work with large data sets
* Processing data using the MapReduce programming technique
* Developing algorithms on your desktop and scaling to a cluster, cloud or Hadoop
To view complete session descriptions and register, visit: https://www.mathworks.com/ukymatlab
Please contact with any questions to:
Tim Mathieu (MathWorks)
Vikram Gazula (UK CCS)