Overview

This webinar shows how to create predictive models for electrical power load forecasting.

MATLAB’s statistics and machine learning toolbox, particularly the regression learner application, will be used to create the models. The script generated from predictive models will then be converted into C/C++ code for enterprise and/or application integration using MATLAB coder and/or embedded coder..

Highlights:

Introduction to Load Forecasting
Introduction to Machine Learning
Creating a Predictive Model using Regression Learner
MATLAB to C/C++ Code Generation

Speaker

Engr. Rodolfo Salvador Jr.

Rod Salvador is a Data Science Application Engineer at TechSource Systems. His fields of specialization are computer vision, signal processing, embedded systems design, machine learning, and deep learning with MATLAB. Before joining TechSource Systems, he worked as a Firmware Engineer for power electronics applications at Emerson Automation Solutions. He also worked as a lecturer for a review center in Manila. Rod holds a bachelor’s degree in Electronics Engineering from AMA University, Quezon City, Philippines. He is currently taking his master’s degree in Electronics and Communications Engineering, with a specialization in artificial intelligence, at De La Salle University, Manila.

Overview

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Speaker

Engr. Rodolfo Salvador Jr.

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