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.- Category:
- Deep Learning,
- Low-Code Apps,
- Machine Learning
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