Deep Learning Fundamentals
Deep Learning Toolbox™ provides tools for each stage of the deep learning workflow.
Preprocess data for deep network training using command-line functions and interactive apps.
Import pretrained networks from MATLAB® or external platforms such as TensorFlow™ 2, TensorFlow-Keras, PyTorch®, and ONNX™.
Build networks using command-line functions or interactively using the Deep Network Designer app.
Select training options and train networks using built-in training functions or custom training loops.
Improve network performance by tuning hyperparameters or running multiple trials using the Experiment Manager app.
Visualize and verify network behavior during and after training.
Export networks to external platforms such as TensorFlow 2 and ONNX.
- Preprocess Data for Deep Neural Networks
Manage and preprocess data for deep learning
- Import Deep Neural Networks
Load built-in pretrained networks and import networks from external platforms
- Build Deep Neural Networks
Build networks using command-line functions or interactively using the Deep Network Designer app
- Train Deep Neural Networks
Train networks using built-in training functions or custom training loops
- Tune Deep Neural Networks
Programmatically and interactively tune training options, resume training from a checkpoint, and investigate adversarial examples
- Visualize and Verify Deep Neural Networks
Visualize network behavior, explain predictions, and verify robustness
- Export Deep Neural Networks
Export networks to external deep learning platforms