Murat Raimbekov

Ultralytics YOLO 🚀

📚 Comprehensive lecture notes for Stanford CS231n: Deep Learning for Computer Vision (2025 Edition) — CNNs, Transformers, Diffusion Models, Vision-Language Models

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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Datasets, Transforms and Models specific to Computer Vision

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Image-based PM2.5 air pollution estimation for Bishkek using urban webcams and deep learning

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The project of the Object-oriented Programming (COM-119) course at AUCA.

The project of the Object-oriented Programming (COM-119) course at AUCA.