yeyun111/dlcv_for_beginners resource

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1505 stars · 629 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Companion code repository for the Chinese book 'Deep Learning and Computer Vision: A Practical Introduction', containing example code across Caffe, MXNet, and PyTorch. It covers beginner-level deep learning tasks such as classification, regression, detection, segmentation, Siamese networks, GANs, and model fusion.

Use cases

• learn deep learning and computer vision from book examples
• train MNIST classifiers with Caffe or MXNet
• build a Siamese network and visualize embeddings with t-SNE
• generate adversarial examples
• train a 2D GAN in PyTorch
• do transfer learning from ImageNet for food classification
• try image segmentation with U-Net in PyTorch
• visualize convolutional kernels and class activation maps

When to choose

• you are a beginner following the book and want runnable example code
• you want to learn classic Caffe or MXNet workflows
• you need simple, self-contained deep learning examples

When to avoid

• you need up-to-date frameworks or modern best practices, as the latter half of the book content is outdated
• you need maintained code with active support, since the repo is no longer updated
• you need production-ready pipelines

Facets

learning-resource · maturity abandoned

machine-learning computer-vision image-processing data-visualization deep-learning computer-vision machine-learning tutorials python cross-platform book-companion-code caffe mxnet pytorch gan siamese-network unet image-classification object-detection image-segmentation beginner-friendly chinese

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