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：
- Linear Classifiers & Logistic Regression线性分类器和逻辑回归
- Predicting sentiment from product reviews情感预测
- Learning Linear Classifiers 线性分类器
- Implementing logistic regression from scratch实现逻辑回归
- Overfitting & Regularization in Logistic Regression过拟合和正则化
- Logistic Regression with L2 regularization L2正则化
- Decision Trees决策树
- Identifying safe loans with decision trees基于决策树的贷款客户信用评估
- Implementing binary decision trees二分决策树的实现
- Preventing Overfitting in Decision Trees防止过拟合
- Decision Trees in Practice决策树的实际应用
- Handling Missing Data处理缺失数据
- Exploring Ensemble Methods集成方法
- Boosting
- Boosting a decision stump
- Precision-Recall 精度和召回率
- Exploring precision and recall
- Scaling to Huge Datasets & Online Learning大数据和在线学习
- 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！！！
