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google-colab

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torchdistill

A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

  • Updated May 25, 2024
  • Python

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

  • Updated May 24, 2024
  • Jupyter Notebook

This repository contains an object detection tutorial to detect swimming pools and cars using YOLOv4-tiny with satellite imagery. The project includes training scripts, dataset configurations, and instructions for running the model on Google Colab.

  • Updated May 22, 2024
  • Python

This project demonstrates image classification on the CIFAR-10 dataset using transfer learning with the pre-trained VGG16 model. The implementation is done in Google Colab and includes data preprocessing, model adaptation, training, evaluation, and result visualization using TensorFlow and Keras.

  • Updated May 19, 2024
  • Jupyter Notebook

Your laboratory for exploring Python's neural networks and beyond. From the very basics of Python to advanced concepts in Machine Learning and Deep Learning, PyMindLab is your gateway to mastering the art of artificial intelligence. Dive in, experiment, and let your mind soar as you unlock the secrets of Python's neural prowess.

  • Updated May 17, 2024

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