CSDN人工智能直通车课程每周作业记录
week1:
- 内容 （线性回归）在Capital Bikeshare （美国 Washington, D.C.的一个共享单车公司）提供的自行车数据上进行回归分析
- 要求 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/%E7%AC%AC%E4%B8%80%E5%91%A8%E4%BD%9C%E4%B8%9A.pdf
- 源码 https://gitee.com/SDMrFeng/first_week_homework
week2:
- 内容 （Logistic 回归&SVM）在Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集）进行分类器练习
- 要求 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/%E7%AC%AC%E4%BA%8C%E5%91%A8%E4%BD%9C%E4%B8%9A.pdf
- 源码 https://gitee.com/SDMrFeng/second_week_operation
week3:
- 内容 在 Rental Listing Inquiries 数据上练习 xgboost 参数调优
- 要求 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/%E7%AC%AC%E4%B8%89%E5%91%A8%E4%BD%9C%E4%B8%9A%E8%A6%81%E6%B1%82.pdf
- 源码 https://gitee.com/SDMrFeng/third_week_operation
week4:
- 内容 使用Event Recommendation Engine Challenge数据集，进行聚类分析
- 要求 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/%E7%AC%AC%E5%9B%9B%E5%91%A8%E4%BD%9C%E4%B8%9A.docx
- 源码 https://gitee.com/SDMrFeng/work_in_the_fourth_week
week5:
- 内容 使用Event Recommendation Engine Challenge数据集，进行Event推荐
- 要求 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/homework5_RS_Event.docx
- 源码 https://gitee.com/SDMrFeng/fifth_weeks_homework
week6:
- 内容：在mnist数据集上训练神经网络
- 源码 https://gitee.com/SDMrFeng/sixth_weeks_homework
- 总结 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/week6.md
week7:
- 内容 在mnist数据集上训练卷积神经⽹络
- 源码 https://gitee.com/SDMrFeng/seventh_weeks_homework
- 总结 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/week7.md
week8:
- 内容 实现一个densenet的网络，并插入到slim框架中进行训练
- 源码 https://github.com/SDMrFeng/quiz-w8-densenet
- 总结 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/week8.md
week9:
- 内容 利用slim框架和object_detection框架，做一个物体检测的模型
- 源码 https://github.com/SDMrFeng/quiz-w9-ssd-mobilenet
- 总结 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/week9.md
week10:
- 内容 以VGG16为基础，构建一个FCN训练模型
- 源码 https://github.com/SDMrFeng/quiz-w10-fcn
- 总结 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/week10.md
week11:
- 内容 使用tensorflow中的rnn相关操作，以作业提供的《全宋词》为训练数据，训练一个人工智能写词机
- 源码 https://github.com/SDMrFeng/quiz-w11-rnn
- 总结 https://github.com/SDMrFeng/CSDN_AI100_HOMEWORK/blob/master/week11.md