Deep Learning Tutorial Series
Updated 5 Dec 2017
The code provides hands-on examples to implement convolutional neural networks (CNNs) for object recognition. The three demos have associated instructional videos that will allow for a complete tutorial experience to understand and implement deep learning techniques.
The demos include:
- Training a neural network from scratch
- Using a pre-trained model (transfer learning)
- Using a neural network as a feature extractor
The corresponding videos for the demos are located here: https://www.mathworks.com/videos/series/deep-learning-with-MATLAB.html
The use of a GPU and Parallel Computing Toolbox™ is recommended when running the examples. Demo 3 requires Statistics and Machine Learning Toolbox™ in addition to the required products below.
MathWorks Deep Learning Toolbox Team (2023). Deep Learning Tutorial Series (https://www.mathworks.com/matlabcentral/fileexchange/62990-deep-learning-tutorial-series), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
- Image Processing and Computer Vision > Computer Vision Toolbox > Recognition, Object Detection, and Semantic Segmentation >
Inspired: Training 3D CNN models
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