ML_classification

本课程共有七周的学习安排：

week1 Welcome引子

week2 Learning Linear Classifiers线性分类

week3 Decision Trees决策树

week4 Preventing Overfitting in Decision Trees防止过拟合

week5 Boosting

week6 Precision-Recall精确度和召回率

week7 Scaling to Huge Datasets & Online Learning大数据和在线学习

共有19个任务：

1. Linear Classifiers & Logistic Regression线性分类器和逻辑回归
2. Predicting sentiment from product reviews情感预测
3. Learning Linear Classifiers 线性分类器
4. Implementing logistic regression from scratch实现逻辑回归
5. Overfitting & Regularization in Logistic Regression过拟合和正则化
6. Logistic Regression with L2 regularization L2正则化
7. Decision Trees决策树
8. Identifying safe loans with decision trees基于决策树的贷款客户信用评估
9. Implementing binary decision trees二分决策树的实现
10. Preventing Overfitting in Decision Trees防止过拟合
11. Decision Trees in Practice决策树的实际应用
12. Handling Missing Data处理缺失数据
13. Exploring Ensemble Methods集成方法
14. Boosting
15. Boosting a decision stump
16. Precision-Recall 精度和召回率
17. Exploring precision and recall
18. Scaling to Huge Datasets & Online Learning大数据和在线学习
19. Training Logistic Regression via Stochastic Gradient Ascent基于梯度上升训练逻辑回归

好的，接下来开始每周课程详细学习~

come on !!!

基础打扎实，找个好工作那都是必须的！！！