一些常用的机器学习算法实现
总体均值、总体方差
样本均值、样本方差
无偏估计、有偏估计
样本标准差
样本协方差、协方差矩阵
Apriori 算法
DesicionTree 算法
HMM模型 Viterbi 算法
针对文本分类的 NaiveBayes 算法
针对文本分类的 LogisticRegression 算法
线性回归算法:
标准的线性回归
局部加权线性回归
岭回归
Keras [1]
TensorFlow [1] [2]
sklearn [1]
Stanford Machine Learning course exercises implemented with scikit-learn
机器学习Sklearn入门指南。Machine Learning Sklearn API and Examples with Python3 and Jupyter Notebook.
A python library to build Model Trees with Linear Models at the leaves.
为机器学习的入门者提供多种基于实例的sklearn、TensorFlow以及自编函数(AnFany)的ML算法程序。
机器学习教程,本教程包含基于numpy、sklearn与tensorflow机器学习,也会包含利用spark、flink加快模型训练等用法。本着能够较全的引导读者入门机器学习。
Personal tasks or codes of Machine Learning and Artificial Intelligence. Practice codes and proje...
Some fundamental machine learning and data-analysis techniques are explained through realistic ex...
Implementations of the machine learning algorithm with Python and numpy
Simple Machine learning API for JavaScript (SKlearn-like API)
Extends scikit-learn with new models, transformers, metrics, plotting.
This repo contains the files created for machine learning using python
Tiny implementation of important algorithms in scikit-learn. Useful when understanding ML algorit...
Implementation of different ML Algorithms from scratch, written in Python 3.x
A repository for recording the machine learning code
This repository consists of all my Machine Learning Projects.