Upcoming Seminar

Data Analytics with MATLAB

Location:
Lisboa
Venue:
Sheraton Lisboa
Date:
31 May 2017
Time:
8:30 – 12:45

Overview

Using Data Analytics to turn large volumes of complex data into actionable information can help you improve engineering 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.

If you are using MATLAB for solving your computational problems, you may also want to extend your impact beyond your desktop, by sharing your custom MATLAB functionality with others. Whether you need to protect your intellectual property or generate readable ANSI C code, MathWorks provides a flexible range of options for sharing your MATLAB programs as C code, executables or software components.

About the Presenter

Lucas García is a Senior Application Engineer at MathWorks specialized in Machine Learning and Big Data. Mathematician by training, he works with MATLAB users across industries to help them solve problems in areas such as Data Analytics and Predictive Maintenance. For several years, he has also been Training Engineer at MathWorks. Prior to joining MathWorks in 2008, he worked as a developer at Indizen and researcher at INE and CSIC-MNCN. His research is focused in the use of neural networks to solve combinatorial optimization problems.

Agenda

Time Title
08:30 - 09:00 Registration
09:00 - 09:15 Welcome and Introduction
09:15 - 10:15 Introduction to MATLAB for Data Analytics
  • Accessing and Preparing Data
    • Accessing data from files, websites, and data warehouses
    • Exploring the data visually to gain insights
    • Cleaning and merging time series data
  • Developing Predictive Models Using Machine Learning
    • Applying neural network, regression trees, and ensemble method
    • Gaining insight into model accuracy and performance
    • Automating model training and report generation
    • Speeding up computation with parallel computing
10:15 - 11:00 Sharing MATLAB based Applications
In this session, we will discuss and demonstrate ways to deploy and share your MATLAB applications and algorithms.
  • Generating standalone MATLAB based applications
  • Packaging MATLAB components for integration with C, C++, Java, .NET and/or Python based applications
  • Scale up your solution to the cloud (e.g. private clouds, Amazon AWS, Microsoft Azure)
11:00 - 11:30 Break
11:30 - 12:30 Tackling Big Data with MATLAB
  • Access data in large text files, databases or from the Hadoop Distributed File System (HDFS)
  • Leverage tall arrays to analyze and process data that does not fit in memory
  • Run algorithms on Spark enabled compute clusters
12:30 - 12:45 Questions and Answers