Machine-Learning-project-with-MLflow-deployment

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 terminal spreadsheet multitool for discovering and arranging data

A python library for decision tree visualization and model interpretation.

Visualize and compare datasets, target values and associations, with one line of code.

Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.

For extensive instructor led learning

An implement of the paper of EDA for Chinese corpus.中文语料的EDA数据增强工具。NLP数据增强。论文阅读笔记。

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

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