rrmaram2000/matlab-toolbox-skills (matlab-deep-learning-v2)

MATLAB Deep Learning Toolbox (R2025b). Functions - trainnet, trainingOptions, unet, unet3d, deeplabv3plus, semanticseg, yolov4ObjectDetector, fasterRCNNObjectDetector, maskrcnn, resnet50, efficientnetb0, imagePretrainedNetwork, dlarray, dlfeval, dlgradient, adamupdate, dlnetwork, imageDatastore, augmentedImageDatastore, minibatchqueue. Tasks - train a deep learning model, classify medical images, build a CNN classifier, segment tumors or organs, detect objects or nodules, fine-tune a pretrained network, transfer learning, create a U-Net, train with custom loss, augment training data, deploy model to ONNX, run training on GPU, build a 3D volumetric network, handle class imbalance. Domains - MRI, CT, X-ray, histopathology, dermatology, retinal imaging, cell detection, lesion segmentation, nodule detection, industrial inspection, autonomous systems, satellite imagery, general computer vision, defect detection, quality control imaging.

Claude Skills are markdown + scripts loaded into Claude Code; scanned with the same pipeline.

Source:

github.com/rrmaram2000/matlab-toolbox-skills

Provenance:

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