Predictive Modeling and Machine Learning with MATLAB

MathWorks via Coursera

Coursera based on 118 ratings

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Overview

Predictive Modeling and Machine Learning with MATLAB is a comprehensive course designed for engineers, data scientists, and analysts who want to apply machine learning techniques using MATLAB’s powerful, built-in tools. This course focuses on building, evaluating, and deploying predictive models in a streamlined, visual, and code-assisted environment. Learners will explore the entire machine learning workflow, including data preprocessing, feature selection, model training, validation, and deployment. Using MATLAB’s Classification Learner and Regression Learner apps, the course enables participants to build models with...

Syllabus

Creating Regression Models

In this module you'll apply the skills gained from the first two courses in the specialization on a new dataset. You'll be introduced to the Supervised Machine Learning Workflow and learn key terms. You'll end the module by creating and evaluating regression machine learning models.

Creating Classification Models

In this module you'll learn the basics of classification models. You'll train several types of classification models and evaluation the results.

Applying the Supervised Machine Learning Workflow

In this module you'll apply the complete supervised machine learning workflow. You'll use validation data inform model creation. You'll apply different feature selection techniques to reduce model complexity. You'll create ensemble models and optimize hyperparameters. At the end of the module, you'll apply these concepts to a final project.