⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

A collection of research papers on decision, classification and regression trees with implementations.

ID3-based implementation of the ML Decision Tree algorithm

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

A curated list of gradient boosting research papers with implementations.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Small JavaScript implementation of ID3 Decision tree

A fast and easy to use decision tree learner in java

机器学习与深度学习算法示例

simple rules engine

A repository for recording the machine learning code

Connected components on multilabel 3D & 2D images. Handles 26, 18, and 6 connected variants.

Ruby Scoring API for PMML

Algorithmic trading using machine learning.

I will update this repository to learn Machine learning with python with statistics content and materials

Solutions to kdd99 dataset with Decision tree and Neural network by scikit-learn

Jupyter Notebooks and miscellaneous

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

TiMBL implements several memory-based learning algorithms.

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

Building Decision Trees From Scratch In Python

Boosted trees in Julia

Essential NLP & ML, short & fast pure Python code

Distilling a Neural Network Into a Soft Decision Tree., Nicholas Frosst, Geoffrey Hinton., 2017.

A python implementation of the CART algorithm for decision trees

Programmable Decision Tree Framework

implement the machine learning algorithms by python for studying

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.