# 机器学习与深度学习
## 机器学习
- [01.k-近邻算法(KNN)](https://blog.csdn.net/wc781708249/article/details/103874381),[KNN-classify.py](./ML/KNN/KNN-classify.py),[KNN-regress.py](./ML/KNN/KNN-regress.py)
- [02.KMean分类(训练数据有标签)](https://blog.csdn.net/wc781708249/article/details/103890932),[kmean-classify.py](./ML/Kmean/kmean-classify.py),[kmean-clustering.py](./ML/Kmean/kmean-clustering.py)
## 深度学习
机器学习与深度学习.zip （94个子文件） 
content dataset 
loan.data 499B trainCG.csv 53KB
test.jpg 39KB iris.data 4KB email spam 
9.txt 161B 13.txt 245B 15.txt 328B 1.txt 235B 14.txt 204B 16.txt 328B 11.txt 402B 5.txt 235B 6.txt 245B 24.txt 328B 25.txt 258B 3.txt 402B 4.txt 226B 19.txt 386B 18.txt 253B 12.txt 182B 20.txt 351B 21.txt 226B 22.txt 351B 7.txt 161B 23.txt 328B 2.txt 291B 8.txt 328B 10.txt 212B 17.txt 241B ham 9.txt 142B 13.txt 164B 15.txt 522B 1.txt 141B 14.txt 162B 16.txt 90B 11.txt 122B 5.txt 113B 6.txt 1KB 24.txt 42B 25.txt 88B 3.txt 364B 4.txt 205B 19.txt 151B 18.txt 168B 12.txt 172B 20.txt 204B 21.txt 229B 22.txt 324B 7.txt 103B 23.txt 598B 2.txt 232B 8.txt 634B 10.txt 82B 17.txt 454B medical_record.data 173B boston.txt 41KB titannic train.csv 59KB test.csv 28KB testSet.txt 2KB DL yolo YOLOV1 loss.py 6KB draw.py 10KB network.py 2KB dataset.py 13KB transforms.py 1KB inference.py 7KB colormap.py 4KB boxes.py 4KB splitData.py 2KB drawResult.py 1KB train.py 6KB py_cpu_nms.py 1KB ML PCA pac.py 2KB Kmean kmean-compress.py 2KB kmean-classify.py 4KB kmean-clustering.py 5KB AdaBoost adaBoost.py 5KB bagging.py 5KB SVM main.py 8KB LinearRegression linearRegression-boston.py 6KB linearRegression.py 4KB KNN KNN-origin.py 3KB KNN-regress.py 5KB KNN-classify.py 4KB softmaxRegression softmaxRegression-iris.py 7KB LogisticRegression logisticRegression-iris.py 6KB logisticRegression-titanic.py 6KB decisionTree decisionTree-iris.py 10KB main.py 10KB decisionTree-titanic.py 9KB naiveBayes bayes-titanic.py 7KB main.py 6KB bayes-iris.py 6KB bayes.py 6KB README.md 444B资源评论
