Machine Learning Tutorial: From Beginner to Advanced

Explore the fundamentals behind machine learning, focusing on unsupervised and supervised learning. You’ll learn what each approach is, and you’ll see the differences between them. In addition, you’ll explore common machine learning techniques including clustering, classification, and regression.

Advanced topics include:  
- Feature engineering for transforming raw data into features that are suitable for a machine learning algorithm.
- ROC curves, for comparing and assessing machine learning results.
- Hyperparameter optimization, so you can find the best set of parameters for a machine learning algorithm.  
- Embedded systems, including best practices for preparing your machine learning models to run on embedded devices.

Learn more about using MATLAB for machine learning: https://bit.ly/3cj8GMc
Get a machine learning MATLAB trial: https://bit.ly/2T5zF6p

--------------------------------------------------------------------------------------------------------
Get a free product trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See what's new in MATLAB and Simulink: https://goo.gl/pgGtod

© 2020 The MathWorks, Inc. MATLAB and Simulink are registered
trademarks of The MathWorks, Inc.
See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

• #science_technology
• #matlab
• #simulink
• #mathworks
• #machine_learning_tutorial
• #what_is_machine_learning
• #machine_learning_algorithms
• #deep_learning
• #machine_learning
• #machine_learning_basics