MATLAB seminars at University of Kentucky - October 22, 2014

Please join the Center for Computational Sciences and MathWorks for complimentary MATLAB seminars on Wednesday, October 22, 2014 in the W.T. Young Library Room B108C.

MATLAB Technical Seminars

Date: Wednesday, October 22
Times: 9:30 12:00 p.m. & 1:30 3:30 p.m.
Location: William T. Young Library Room #B108C University of Kentucky

To register please click here

Our event features a technical session presented by a MathWorks engineer:

9:30am - 12:00pm
Session 1: Data Mining and Machine Learning with MATLAB
Discovering patterns in large data sets involves methods at the intersection of machine learning, statistics, and database systems. The overall goal is the extraction of patterns and other meaningful information that can be transformed into an understandable structure for future use.

In this session we demonstrate methods for optimally importing, manipulating, visualizing and mining data sets in MATLAB. We also demonstrate machine learning algorithms for the purpose of building predictive models and discovering useful patterns in observed data.

Highlights include:
* Importing and working with large data sets
* Detecting patterns using visualization techniques
* Gaining insight into your data using descriptive statistics
* Applying supervised and unsupervised learning algorithms
* Developing and sharing standalone executables and software Components

Please click here to download demo and PDF files.

1:30pm - 3:30pm
Session 2: Optimizing and Accelerating Your MATLAB Code
Large-scale simulations and data processing tasks that support engineering and scientific activities such as mathematical modeling, algorithm development, and testing can take an unreasonably long time to complete or require a lot of computer memory. You can speed up these tasks by taking advantage of high-performance computing resources, such as multicore computers, GPUs, computer clusters and cloud computing services. In this session you will learn how to boost the execution speed of computationally and data-intensive problems using MATLAB and the Parallel Computing Toolbox.

In this session you will learn how to boost the execution speed of computationally and data-intensive problems using MATLAB and the Parallel Computing Toolbox. We will introduce and demonstrate the high-level programming constructs that allow you to easily create parallel MATLAB applications without low-level programming and finally talk about tools to automatically translate your MATLAB code into C.

Highlights include:
* Toolboxes with built-in algorithms for parallel computing
* Creating parallel applications to speed up independent tasks
* Scaling up to computer clusters, grid environments or clouds
* Employing GPUs to speed up your computations
* Automatically generating portable C code from MATLAB

Please click here to download demo and PDF files.

To view complete session descriptions and register, visit: https://www.mathworks.com/company/events/seminars/seminar95305.html
Please contact Tom McHugh (MathWorks) or Vikram Gazula (UK CCS) with any questions at tom.mchugh@mathworks.com or gazula@ccs.uky.edu