ZHANG Xinyun's repositories
cmu213_attacklab
attack lab
cmu213_bomblab
cmu213 bomblab
cmu213_datalab
cmu213_datalab
CRAFT-pytorch
Official implementation of Character Region Awareness for Text Detection (CRAFT)
deep-text-recognition-benchmark
Text recognition (optical character recognition) with deep learning methods.
PyramidBox
This repo implements PyramidBox with pytorch
Pyramidbox.pytorch
Pyramidbox implement with pytorch
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
pytorch1.0-cn
PyTorch 1.0 官方文档 中文版，欢迎关注微信公众号：磐创AI
SRN
Selective Refinement Network for High Performance Face Detection, AAAI, 2019
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
XGBoost-Tutorial-for-Beginners
One of the most common questions we get on Data science is: How can we provide better solutions than other machine learning algorithms? If you get confused and ask experts what should you learn at this stage, most of them would suggest / agree that you go ahead with ensemble learning?