An Introduction to Data Analytics and Machine Learning
We are delighted to offer the following three-day industrial training course at our training facility in Houston on June 15-17.
For registration please visit http://viascorp.com/vias/course-schedule/?ctype=1.
We are an authorized education partner of Dassault Systèmes and we can offer Abaqus SIMULIA training courses in house or at your facility.
VIAS provides integrated, innovative, and cost-effective engineering and software solutions to Energy Process and Utilities industry.
Title: An Introduction to Data Analytics and Machine Learning
Date: June 15-17
Hours: 9 AM - 5 PM (CST)
Location: VIAS Houston Office,
1400 Broadfield Blvd. Suite 325, Houston, TX 77084
Data Analytics provides the technology to build data-driven predictive models and to search for interesting patterns in large amounts of data. At the core of data analytics lays the field of Machine Learning, which provides all the conceptual infrastructure and algorithms to build computer systems that learn from experience. Machine Learning is a subfield of Artificial Intelligence; it has received unprecedented attention lately due to its use in many real world applications.
The course will explain how to build systems that learn and adapt borrowing from examples in industry and science, e.g.
- learning to predict medical diagnoses,
- anticipating machine failures,
- minimizing the cost of expensive simulations
The class will be self-contained (no previous knowledge will be assumed). Main topics include:
- linear discriminants
- neural networks
- deep learning
- feature selection
- decision trees
- support vector machines
- unsupervised learning
Target Audience: This course is recommended for everyone interested in data analytics and machine learning.
Instructor: Dr. Ricardo Vilalta
Dr. Ricardo Vilalta is associate professor in the Department of Computer Science at the University of Houston. Prior to that appointment he was a researcher at IBM T.J. Watson Center in New York. He holds MS and Ph.D. degrees in computer science from the University of Illinois at Urbana-Champaign. His research interests are in machine learning, statistical learning theory, data mining, and artificial intelligence. He is recipient of the Fulbright scholarship (1991-97); the Invention Achievement Award from IBM Research (2001); Best Paper Award at the European Conference on Machine Learning (2003); and the CAREER Award from National Science Foundation (2005).
Event Type: Seminar
Location: Houston The USA
Date: June 15, 2016