/Hands-On-Machine-Learning

Implementation of Bayes method, KNN, Logistic Regression, SVM, K-Means and Collaborative Filtering

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Hands-On-Machine-Learning

  • Estimate the author of 12 controversial Federalist Papers using Bayes Decision
  • Using KNN, Logistic Regression, SVM and K-Means methods to classify 500 multi-calss points with Gaussion distribution
  • Simple recommendation system for Netflix's user, using Latent Factors Model and Neighborhood Methods
  • Analyze data using the linear regression techniques (ridge regression and pth-order polynomial regression) to predict the miles per gallon a car will get using six quantities (features) about that car
  • Predict spam using Naive Bayes Classifier and Logistic Regression

机器学习实战:

  • 用贝叶斯决策的方法推测12篇存在争议的《联邦党人文集》的作者
  • 分别用KNN、逻辑回归、SVM、K-Means方法对二维高斯分布的两类点(500个)进行分类并绘制分类边界线
  • 分别用潜在因子算法(矩阵分解)、临近相似度算法,实现协同滤波,根据一个涉及影评者及其几部影片评分情况的字典,对用户进行电影推荐