├── Base ├── books │ ├── JTZHBC │ │ ├── 2.recommendation │ │ │ └── recommendations.py │ │ ├── 3.discovery │ │ │ ├── 3test.py │ │ │ ├── clusters.py │ │ │ └── generatefeedvector.py │ │ ├── 4.searchengine │ │ │ ├── nn.py │ │ │ └── searchengine.py │ │ ├── 5.optimization │ │ │ ├── dorm.py │ │ │ ├── optimization.py │ │ │ ├── socialnetwork.py │ │ │ └── test.py │ │ └── readme.md │ └── ML_in_action │ │ ├── AdaBoost │ │ ├── adaboost.py │ │ └── test.py │ │ ├── Bayes │ │ ├── bayes.py │ │ └── test.py │ │ ├── DecisionTree │ │ ├── test.py │ │ ├── treePlotter.py │ │ └── trees.py │ │ ├── Logistic │ │ ├── logRegres.py │ │ ├── test.py │ │ └── testSet.txt │ │ ├── Regression │ │ ├── regression.py │ │ └── test.py │ │ ├── SVM │ │ ├── svm.py │ │ └── test.py │ │ ├── kMeans │ │ ├── kMeans.py │ │ └── test.py │ │ ├── kNN │ │ ├── kNN.py │ │ └── test.py │ │ └── readme.md ├── challenge │ ├── AIchallenge │ │ ├── AI_pic2text_pre.ipynb │ │ ├── AI_pic2text_pre2.ipynb │ │ └── AI_pic2text_pre3.ipynb │ ├── DataFountain │ │ └── writing_classify │ │ │ └── pre_1.ipynb │ ├── biendata │ │ └── mobike │ │ │ ├── example_learn_mobike.ipynb │ │ │ └── mobike_mine.ipynb │ ├── kaggle │ │ ├── HousePrices │ │ │ ├── House Prices.ipynb │ │ │ ├── predictions.csv │ │ │ ├── test.csv │ │ │ └── train.csv │ │ ├── Titanic │ │ │ ├── Titanic.ipynb │ │ │ ├── pre.csv │ │ │ ├── test.csv │ │ │ └── train.csv │ │ ├── readme.md │ │ └── searchrelevance.pdf │ └── tianchi │ │ └── shop_location │ │ ├── baseline1.ipynb │ │ ├── baseline2.ipynb │ │ └── shop_pre1.ipynb ├── courses │ ├── DL_AndrewNg │ │ ├── .DS_Store │ │ ├── README.md │ │ ├── course1 │ │ │ ├── BuildingDNNv3.ipynb │ │ │ ├── DNNApplicationv3.ipynb │ │ │ ├── LRwithNN.ipynb │ │ │ └── week3NN.ipynb │ │ ├── course2 │ │ │ ├── GradientChecking.ipynb │ │ │ ├── Initialization.ipynb │ │ │ ├── OptimizationMethods.ipynb │ │ │ ├── Regularization.ipynb │ │ │ └── TensorflowTutorial.ipynb │ │ ├── course4 │ │ │ ├── .DS_Store │ │ │ ├── ArtGenerationwithNeuralStyleTransfer2.ipynb │ │ │ ├── AutonomousdrivingapplicationCardetectionv3.ipynb │ │ │ ├── ConvolutionmodelApplicationv1.ipynb │ │ │ ├── ConvolutionmodelStepbyStepv2.ipynb │ │ │ ├── FaceRecognitionfortheHappyHousev3.ipynb │ │ │ ├── KerasTutorialHappyHousev2.ipynb │ │ │ └── ResidualNetworksv2.ipynb │ │ └── course5 │ │ │ ├── .DS_Store │ │ │ ├── BuildingaRecurrentNeuralNetworkStepbyStepv3.ipynb │ │ │ ├── DinosaurusIslandCharacterlevellanguagemodelfinalv3.ipynb │ │ │ ├── Emojifyv2.ipynb │ │ │ ├── ImproviseaJazzSolowithanLSTMNetworkv3.ipynb │ │ │ ├── Neuralmachinetranslationwithattentionv3.ipynb │ │ │ ├── Operationsonwordvectorsv2.ipynb │ │ │ ├── Triggerworddetectionv1.ipynb │ │ │ └── rnn_utils.py │ ├── coursera_ML │ │ ├── ex1_liner │ │ │ ├── computeCost.m │ │ │ ├── ex1.m │ │ │ └── gradientDescent.m │ │ ├── ex2_logistc │ │ │ ├── costFunction.m │ │ │ ├── costFunctionReg.m │ │ │ ├── ex2.m │ │ │ ├── ex2_reg.m │ │ │ ├── plotData.m │ │ │ ├── predict.m │ │ │ └── sigmoid.m │ │ ├── ex3_nn │ │ │ ├── lrCostFunction.m │ │ │ ├── oneVsAll.m │ │ │ ├── predict.m │ │ │ └── predictOneVsAll.m │ │ └── readme.md │ ├── cs231n │ │ ├── README.md │ │ ├── assignment1 │ │ │ ├── .gitignore │ │ │ ├── .ipynb_checkpoints │ │ │ │ ├── features-checkpoint.ipynb │ │ │ │ ├── knn-checkpoint.ipynb │ │ │ │ ├── softmax-checkpoint.ipynb │ │ │ │ ├── svm-checkpoint.ipynb │ │ │ │ └── two_layer_net-checkpoint.ipynb │ │ │ ├── README.md │ │ │ ├── collectSubmission.sh │ │ │ ├── cs231n │ │ │ │ ├── __init__.py │ │ │ │ ├── classifiers │ │ │ │ │ ├── __init__.py │ │ │ │ │ ├── k_nearest_neighbor.py │ │ │ │ │ ├── linear_classifier.py │ │ │ │ │ ├── linear_svm.py │ │ │ │ │ ├── neural_net.py │ │ │ │ │ └── softmax.py │ │ │ │ ├── data_utils.py │ │ │ │ ├── datasets │ │ │ │ │ ├── .gitignore │ │ │ │ │ └── get_datasets.sh │ │ │ │ ├── features.py │ │ │ │ ├── gradient_check.py │ │ │ │ └── vis_utils.py │ │ │ ├── features.ipynb │ │ │ ├── frameworkpython │ │ │ ├── knn.ipynb │ │ │ ├── setup_googlecloud.sh │ │ │ ├── softmax.ipynb │ │ │ ├── start_ipython_osx.sh │ │ │ ├── svm.ipynb │ │ │ └── two_layer_net.ipynb │ │ └── note │ │ │ └── inverted_dropout.py │ └── qiyuezaixian │ │ ├── .DS_Store │ │ ├── README.md │ │ ├── course1 │ │ ├── PythonRegEx.html │ │ ├── jieba.html │ │ └── string_operation.ipynb │ │ ├── course2 │ │ ├── Ngram.html │ │ ├── bayes.html │ │ ├── bayesClassfierNews.html │ │ ├── bayesDetector.html │ │ └── stopwords_cn.txt │ │ ├── course3 │ │ └── HillaryEmail.ipynb │ │ └── course5 │ │ └── HMM_POS_TAG.html ├── frameworks │ ├── caffe │ │ ├── code │ │ │ ├── ssd_detection_output_layer.py │ │ │ └── test_ssd.py │ │ ├── docs │ │ │ └── ubuntu18_anaconda3_py27_cpu_COMPILE_CAFFE.md │ │ ├── project │ │ │ └── caffe_ssd_write_layer │ │ │ │ ├── 3.jpg │ │ │ │ ├── caffe_ssd_deploy.prototxt │ │ │ │ ├── caffe_ssd_deploy2.prototxt │ │ │ │ ├── dog_bike_car.jpg │ │ │ │ ├── img │ │ │ │ └── two_faces_300.jpg │ │ │ │ ├── nnie_ssd_deploy.prototxt │ │ │ │ ├── res.jpg │ │ │ │ ├── res222.jpg │ │ │ │ ├── test_caffe_ssd.py │ │ │ │ ├── test_img.jpg │ │ │ │ ├── test_img2.jpg │ │ │ │ ├── test_img3.jpg │ │ │ │ ├── test_ssd_concat.py │ │ │ │ ├── test_ssd_detection_output.py │ │ │ │ ├── test_ssd_priorbox.py │ │ │ │ ├── test_ssd_priorbox_originSSD.py │ │ │ │ ├── two_faces_300.jpg │ │ │ │ ├── yufacedetectnet-open-v1-concat.prototxt │ │ │ │ ├── yufacedetectnet-open-v1-detection_output.caffemodel │ │ │ │ ├── yufacedetectnet-open-v1-detection_output.prototxt │ │ │ │ ├── yufacedetectnet-open-v1-priorbox.prototxt │ │ │ │ ├── yufacedetectnet-open-v1.caffemodel │ │ │ │ ├── yufacedetectnet-open-v1.prototxt │ │ │ │ ├── yufacedetectnet-open-v1_my.caffemodel │ │ │ │ ├── yufacedetectnet-open-v1_my.prototxt │ │ │ │ ├── yufacedetectnet-open-v1_new.caffemodel │ │ │ │ └── yufacedetectnet-open-v1_new.prototxt │ │ └── readme.md │ ├── keras │ │ ├── .DS_Store │ │ ├── baseline │ │ │ ├── main.py │ │ │ ├── my_data.py │ │ │ └── my_model.py │ │ ├── data │ │ │ ├── 0_0.png │ │ │ └── 2_100.png │ │ ├── demo │ │ │ ├── .DS_Store │ │ │ ├── Keras_GAN.ipynb │ │ │ ├── RNN_classify.ipynb │ │ │ ├── Word_Language_Modelling_LSTM.ipynb │ │ │ ├── cam_heatmap.py │ │ │ ├── classify_focal_loss.py │ │ │ ├── clearData.py │ │ │ ├── data_aug.py │ │ │ ├── data_generator.py │ │ │ ├── fmeasure_metric.py │ │ │ ├── h5_customer_to_tflite.py │ │ │ ├── h5_to_ckpt.py │ │ │ ├── h5_to_pb.py │ │ │ ├── h5_to_tflite.py │ │ │ ├── keras_cifar10.ipynb │ │ │ ├── keras_mnist.ipynb │ │ │ ├── keras_net.py │ │ │ ├── layer_trainable.py │ │ │ ├── lstm_word_embedding.ipynb │ │ │ ├── multi_output_class_weight.py │ │ │ ├── pretrain.py │ │ │ ├── show_keras_data.py │ │ │ └── tflite_pre.py │ │ ├── keras_example.ipynb │ │ ├── note │ │ │ ├── .DS_Store │ │ │ └── keras_multiGPU.md │ │ ├── project │ │ │ ├── .DS_Store │ │ │ ├── 3D_predict.py │ │ │ ├── Caipiao_nn.ipynb │ │ │ ├── history3D.txt │ │ │ └── plate_color.ipynb │ │ └── readme.md │ ├── mxnet │ │ └── load_pre_demo.py │ ├── pytorch │ │ ├── IOU_balanced.py │ │ ├── IoU_loss.py │ │ ├── demo │ │ │ ├── CEloss.py │ │ │ ├── onnx_pre.py │ │ │ └── show_pth_data.py │ │ ├── practice │ │ │ ├── 60分钟入门PyTorch-0.目录.ipynb │ │ │ ├── 60分钟入门PyTorch-1.PyTorch是什么？.ipynb │ │ │ ├── 60分钟入门PyTorch-2.AUTOGRAD.ipynb │ │ │ ├── 60分钟入门PyTorch-3.神经网络.ipynb │ │ │ ├── 60分钟入门PyTorch-4.训练一个分类器.ipynb │ │ │ ├── 60分钟入门PyTorch-5.数据并行.ipynb │ │ │ ├── gan_pytorch.py │ │ │ ├── mnist_demo.py │ │ │ ├── pytorch_example.ipynb │ │ │ └── pytorch_lstm.ipynb │ │ └── readme.md │ └── tensorflow │ │ ├── .DS_Store │ │ ├── basic │ │ ├── .DS_Store │ │ ├── Learn_tf.ipynb │ │ ├── TFLiteModelMaker │ │ │ ├── README.md │ │ │ └── train.py │ │ ├── TensorFlowExample.ipynb │ │ ├── ckpt2pb.py │ │ ├── ckpt_pre.py │ │ ├── onnx_pre.py │ │ ├── pb2tflite.py │ │ ├── pruned_demo.py │ │ ├── read_pb.py │ │ ├── tf_pb_pre.py │ │ ├── tf_save_load.ipynb │ │ ├── tflite_pre.py │ │ └── tflite_show_middle_output.py │ │ ├── demo │ │ ├── .DS_Store │ │ ├── TF_logsitic.ipynb │ │ ├── basic_mnist_demo.py │ │ ├── mnist_cnn_demo.py │ │ └── ten_people_face_reconize │ │ │ ├── .DS_Store │ │ │ ├── main.py │ │ │ ├── model │ │ │ └── .DS_Store │ │ │ ├── olivettifaces.gif │ │ │ └── result.png │ │ └── readme.md └── tools │ ├── lightgbm │ ├── readme.md │ ├── simpleexample.py │ └── sklearnexample.py │ ├── scikit-learn │ ├── .DS_Store │ ├── README.md │ ├── choose.png │ ├── demo │ │ ├── kmeans_color.py │ │ └── tSNE.py │ ├── ex2data1.txt │ ├── pearsonr.ipynb │ ├── sklearn_LR.py │ └── useful.py │ ├── spark │ ├── .DS_Store │ ├── README.md │ ├── learnsparkLDA │ │ ├── .DS_Store │ │ ├── learn_sparkRDD.ipynb │ │ ├── spark_MLlib.ipynb │ │ ├── spark_pairRDD.ipynb │ │ ├── spark_saveload.ipynb │ │ └── spark_uplevel.ipynb │ └── start.py │ └── xgboost │ ├── readme.md │ ├── xgboost.ipynb │ └── xgboost_multi.ipynb ├── CV ├── codes │ ├── IOU.py │ ├── flickr_to_voc.py │ ├── label_smoothing.py │ ├── makeVOCDirs.py │ ├── nms.py │ ├── pascalVOC2csv.py │ ├── show_voc_box.py │ ├── simple_mixup.py │ ├── to_coco_person17.py │ ├── txt2xml.py │ └── updateTXT.py ├── knowledge.md ├── nets │ ├── .DS_Store │ ├── alexnet │ │ ├── .DS_Store │ │ ├── README.md │ │ ├── alexnet.jpg │ │ └── keras_alexnet.py │ ├── lenet5 │ │ ├── .DS_Store │ │ ├── README.md │ │ ├── keras_lenet5.py │ │ └── lenet5.jpg │ └── vgg │ │ ├── .DS_Store │ │ ├── README.md │ │ ├── keras_vgg.py │ │ ├── vgg.jpg │ │ └── vgg16.jpg └── note │ ├── .DS_Store │ ├── DCNN_book_note.md │ ├── chineseocr-ctpn-densenet.md │ ├── cptn.jpg │ ├── ctc.jpg │ ├── denseblock.jpg │ ├── densenet.jpg │ ├── handwrite_ocr_note.md │ ├── nms.jpg │ ├── vgg1.jpg │ ├── vgg2.jpg │ ├── vgg3.jpg │ └── vgg4.jpg ├── DIY ├── .DS_Store ├── Adaboost.ipynb ├── CRF.ipynb ├── DecisionTree.ipynb ├── EM.ipynb ├── HMM.ipynb ├── IOU.py ├── LR.ipynb ├── NN.ipynb ├── NaiveBayes.ipynb ├── PCA.ipynb ├── ROC_AUC.ipynb ├── SVM.ipynb ├── Stacking.py ├── ex1_py_liner.ipynb ├── ex1data1.txt ├── kMeans.ipynb ├── kNN.ipynb ├── lenses.txt ├── perceptron.ipynb ├── tryStacking.ipynb └── yoloF1.py ├── DM ├── knowledge.md └── note │ ├── .DS_Store │ ├── FeatureEngneering.md │ └── img │ └── fe.jpg ├── NLP ├── 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