This project is one of my homeworks in Big Data Lesson .
这是我的2017大数据课的作业。老师提供一组包含学生成绩与校园卡消费记录的数据。我对数据进行预处理后，分别采用神经网络、线性回归和SVM方法对学生学习成绩进行了回归。准确率为78%。
结果表明，学生经常去图书馆自习、每天在食堂吃饭不超过16块且前3学期学习成绩达到优秀的学生，在第4学期很可能再次达到优秀。该结果只针对次数据集。
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numpy
sklearn
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[大数据课程作业]分别采用神经网络、线性回归、SVM方法预测学生成绩
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