Machine-Learning-Rare-Event-Classification

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

A python library for decision tree visualization and model interpretation.

Easily compute clip embeddings and build a clip retrieval system with them

For extensive instructor led learning

JVector: the most advanced embedded vector search engine

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

Blazing fast framework for fine-tuning similarity learning models

Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet