-
FastDup is a tool for gaining insights from a large image collection. It can find anomalies, duplicate and near duplicate images, clusters of similaritity, learn the normal behavior and temporal interactions between images. It can be used for smart subsampling of a higher quality dataset, outlier removal, novelty detection of new information to be sent for tagging. FastDup scales to millions of images running on CPU only.
🚀 Github 镜像仓库🚀 源项目地址
⬇ ⬇ ⬇ -
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
🚀 Github 镜像仓库🚀 源项目地址
⬇ ⬇ ⬇ -
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
🚀 Github 镜像仓库🚀 源项目地址
⬇ ⬇ ⬇ -
Interview = 简历指南 + 算法题 + 八股文 + 源码分析
🚀 Github 镜像仓库🚀 源项目地址
⬇ ⬇ ⬇ -
kaggle kernel for Titanic dataset
🚀 Github 镜像仓库🚀 源项目地址
⬇ ⬇ ⬇