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MATLAB: Using MATLAB for Machine Learning
Dive into machine learning in MATLABPreview the first lesson free — get full access to all 3 lessons.
Advanced Provider : Gabriel Popoola 3 Lessons · 20m in Arabic, German, English, Spanish, French, Portuguese, Chinese
Course Description
Machine learning is an advanced and popular area in science and mathematics. The process of building a good machine learning model is iterative and can be somewhat tedious. The effort required to build a model that is accurate and robust is non-trivial. Training and optimizing models, tuning parameters, and selecting the essential and valuable features can be tedious and complicated tasks to carry out. I'm going to go over hyperparameter tuning with auto animals, specifically as it pertains to model selection using Bayesian optimization. We will go over reducing the number of features in order to perform classification. In this MATLAB module, you will discover how MATLAB can be used for machine learning (ML) in MATLAB using AutoML.
After completing this module, you will be able to apply what you learned to any project or task involving machine learning. It can be helpful in the private sector, government, and even academia. Additionally, it can be applied to any personal or home projects that you are working on, such as a smart home or smart home system.
What You'll Learn
- Understand how MATLAB can be used for machine learning
- Explain the importance of data and features in machine learning
- Define the concept of hyperparameter tuning
- Apply automatic machine learning (AutoML) in MATLAB
- Perform feature selection to reduce the number of features for classification
- Use Bayesian optimization for model selection during hyperparameter tuning
Key Takeaways
- Building a good machine learning model is an iterative process that requires non-trivial effort to make a model accurate and robust.
- Training and optimizing models, tuning parameters, and selecting valuable features can be tedious and complicated tasks.
- MATLAB can be used to perform machine learning through AutoML, including hyperparameter tuning and model selection with Bayesian optimization.
- Reducing the number of features through feature selection can be used to perform classification.
- Skills learned in this module can be applied to projects in the private sector, government, academia, and personal projects such as a smart home system.
Frequently Asked Questions
What will I learn in this MATLAB machine learning course?
You will discover how MATLAB can be used for machine learning using AutoML, learn the importance of data and features, and understand the concept of hyperparameter tuning, including model selection using Bayesian optimization and feature selection for classification.
What topics does this module cover?
The module covers automatic machine learning in MATLAB (AutoML), feature selection, and hyperparameter tuning.
Where can I apply what I learn in this course?
After completing the module, you can apply what you learned to any project or task involving machine learning, including in the private sector, government, academia, and personal or home projects such as a smart home system.
What skills does this course help develop?
This course helps develop skills in Automated Machine Learning, Google AutoML, Machine Learning, Machine Learning Algorithms, Machine Learning Methods, and MATLAB.
