Artificial Intelligence

Apply machine learning and deep learning

New AI Examples in R2022b

There are many new examples for AI in the latest version of MATLAB R2022b. These examples show you how to use the new features, but also guide you in applying machine learning and deep learning to new domains.
We have selected few of the newly-published examples below, and grouped them by feature category. To view all the new AI features and examples, go to new machine learning features and new deep learning features.

Low-Code AI

AI and Model Training

Hardware-Aware AI

Use apps to interactively build, train, assess, and compare AI models. Discovery new algorithms for creating AI models with high prediction accuracy. Create, optimize, and deploy AI systems to hardware platforms
Export Image Classification Network from Deep Network Designer to Simulink Train Network with Complex-Valued Data Compress Machine Learning Model for Memory-Limited Hardware
Visualize and Assess Classifier Performance in Classification Learner Train Bayesian Neural Network Code Generation for Anomaly Detection

AI Applications

The following examples are applying machine learning and deep learning techniques to application-specific workflows.
Predict Battery State of Charge Using Machine Learning Brain MRI Segmentation Using Pretrained 3-D U-Net Network

Audio-Based Anomaly Detection for Machine Health Monitoring Explore Fairness Metrics for Credit Scoring Model

I hope you found these examples informative and helpful. Which new AI method or workflow are you most eager to try out for your application? Leave us a comment below.
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