What's New in Data Analytics
Explore the latest MATLAB® functions and features for developing machine learning models, working with big data, and operationalizing analytics to production systems.
MATLAB® capabilities address major data analytics challenges such as:
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Accessing and exploring data from a variety of sources including databases, data warehouses, and Hadoop
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Cleaning data with preprocessing techniques such as PCA and feature selection
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Developing advanced analytics with machine learning and optimization
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Integrating analytics with enterprise systems, clusters, and clouds
WHY MATLAB?
The engineers choose MATLAB to build advanced analytics systems, ranging from predictive maintenance to automated driving, using features like:
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Native support for sensor, image, video, telemetry, and other real-time formats
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Big data functionality for Hadoop® and Spark™ and ODBC/JDBC databases
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Prebuilt statistics and machine learning algorithms
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High-speed processing of large data sets
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Integration into enterprise systems and clouds
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Support for targeting real-time embedded hardware
Data Analytics training program
Introduction to MATLAB & Simulink for Engineering Applications
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The MATLAB Live Editor provides a new way to create, edit, and run MATLAB code. See your results together with the code that produced them. Add equations, images, hyperlinks, and formatted text to enhance your narrative. Share with others as interactive documents.
Duration : 3 days
If you would like to join any courses. Please contact us.
This two-day course focuses on data analytics and machine learning techniques in MATLAB® using functionality within Statistics and Machine Learning ToolboxTM and Neural Network ToolboxTM. The course demonstrates the use of unsupervised learning to discover features in large data sets and supervised learning to build predictive models. Examples and exercises highlights techniques for visualization and evaluation of results.
Duration : 2 days
If you would like to join any courses. Please contact us.
The four-day hands-on course focuses on data analytics and machine learning techniques in MATLAB® using functionality within Statistics and Machine Learning Toolbox™ and Neural Network Toolbox™. The course demonstrates the use of appropriate MATLAB and Statistics and Machine Learning Toolbox functionality throughout the analysis process; from importing and organizing data, to exploratory analysis, to confirmatory analysis and simulation as well as the use of unsupervised learning to discover features in large data sets and supervised learning to build predictive models. Examples and exercises highlight techniques for visualization and evaluation of results.
Duration : 4 days
If you would like to join any courses. Please contact us.
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Engineers and Scientists Worldwide Rely on MATLAB
ASML
“As a process engineer I had no experience with neural networks or machine learning. I couldn’t have done this in C or Python. It would’ve taken too long to find, validate, and integrate the right packages.”
MIT
“MATLAB is the language used by virtually every team in the world that designs gravitational wave detectors… I look forward to exploring the data from each new detection in MATLAB.”
- Matthew Evans, Assistant Professor of Physics
Delphi Automotive
“MATLAB is my preferred tool because it speeds algorithm design and improvement. I can generate C code that is reliable, efficient, and easy for software engineers to integrate within a larger system.”
- Liang Ma, Systems Engineer
- Emil Schmitt-Weaver, Development Engineer
