Practical Deep Learning Examples with MATLAB

Familiar with the basics and ready to apply deep learning with MATLAB®? Get started with the hands-on examples in this ebook. You'll learn three approaches to training neural networks for image classification:

  1. Training a network from scratch

  2. Using transfer learning to train an existing network

  3. Adapting a pretrained network for semantic segmentation

 

You'll also see two examples showing how deep learning models can be applied to time series or signal data.

Download the ebook and learn how to:

  • Create and configure network layers

  • Adapt network architectures, including convolutional neural network (CNN), directed acyclic graph (DAG), and long short-term memory (LSTM)

  • Select the best training options and algorithms

  • Use data augmentation and Bayesian optimization to improve training accuracy

  • Incorporate spectrograms for speech recognition

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MATLAB for Deep Learning

Explore MATLAB solutions for deep learning, including videos, product capabilities, examples, and models.

Get ebook Introducing Deep Learning with MATLAB

Explore deep learning fundamentals in this MATLAB ebook.

 
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