Machine Learning

Machine learning is the study of using mathematical models to help a computer to analyze data and learn directly from experience, without being explicitly programmed to do so. It is considered as a sub-cluster of artificial intelligence.

Using MATLAB, engineers and other domain experts have deployed thousands of machine learning applications. MATLAB makes the hard parts of machine learning easy with:

Point-and-click apps for training and comparing models
Advanced signal processing and feature extraction techniques
Automatic machine learning (AutoML) including feature selection, model selection and hyperparameter tuning
The ability to use the same code to scale processing to big data and clusters
Automated generation of C/C++ code for embedded and high-performance applications
Integration with Simulink as native or MATLAB Function blocks, for embedded deployment or simulations
All popular classification, regression, and clustering algorithms for supervised and unsupervised learning
Faster execution than open source on most statistical and machine learning computations

What is Machine Learning e-book

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This free, two-hour tutorial provides an interactive introduction to practical machine learning methods for classification problems.

Machine Learning Onramp

Automated Machine Learning (AutoML)

Automatically generate features from training data and optimize models using hyperparameter tuning techniques such as Bayesian optimization. Use specialized feature extraction techniques such as wavelet scattering for signal or image data, and feature selection techniques such as neighborhood component analysis (NCA), sequential feature selection.

Machine Learning with Finance Sector video

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Code Generation and Simulink Integration

Deploy statistics and machine learning models to embedded systems and generate readable C or C++ code for your entire machine learning algorithm, including pre and post processing steps. Accelerate verification and validation of your high-fidelity simulations using machine learning models through MATLAB function blocks and native blocks in Simulink.

Augmented Learning with MATLAB e-book

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Big Data with MATLAB e-book

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Scaling & Performance

Use tall arrays train machine learning models to data sets too large to fit in memory, with minimal changes to your code. You can also speed up statistical computations and model training with parallel computing on your desktop, on clusters, or on the cloud.