Deep Learning with MATLAB

Etkinlik Programı ve İçeriği

  • Data preparation

  • Handling of large data sets (images, signals, text, …)

  • Partially automated data labeling and synthetic data generation

  • AI modeling

  • Create deep learning models from scratch for image and signal data.

  • Hyperparameters optimization using Bayesian optimization

  • Tracking and running modeling runs with the Experiment Manager app for rapid, automated iteration

  • Accelerate training locally or in the cloud by relying on GPUs

  • Import and export models from Python frameworks such as Keras and PyTorch.

  • Introducing the extended deep learning framework to customize and train advanced neural networks

  • Deployment

  • Automatic generation of CUDA and C++ code for embedded targets.

  • Deploying your models to production in a variety of formats

Etkinlik Bilgileri

17 Kasım 2010
Moubarak Gado
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