What’s New in MATLAB for Deep Learning?

MATLAB makes deep learning easy and accessible for every application. Discover the top new features and examples in deep learning, plus the latest in related toolboxes for designing and building your deep learning solutions.

R2020b Highlights for Deep Learning

Deep Learning Simulink Support

Incorporate deep learning models into Simulink for simulation and code generation.

 

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Experiment Manager App

Manage and train multiple deep learning experiments, keep track of training parameters, and analyze and compare results and code.

 

>>Learn more

New examples for deep learning in latest release:

Explore Related Applications for Deep Learning

Reinforcement Learning

Design and train policies with functions and blocks using algorithms, including DQN, A2C, and DDPG.

GPU Coder

Generate code for deep networks including code for custom layers.

Advanced Deep Learning Network Architectures

Design and train custom algorithms for networks such as GANs, Autoencoders, and Siamese networks.

 

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Deep Learning for Signal and Audio

Design deep learning models for use in signal processing and audio applications.

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Want the full story?

Check out deep learning blog posts for R2019a, R2019b, and R2020a

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Have Questions About Using MATLAB for Deep  Learning

30 Days of Exploration at Your Fingertips

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