├── MachinLN ├── README.md ├── 机器学习-001：MachineLN之三要素.md ├── 机器学习-002：MachineLN之模型评估.md ├── 机器学习-003：MachineLN之dl.md ├── 机器学习-004：DeepLN之CNN解析.md ├── 机器学习-005：DeepLN之CNN权重更新（笔记）.md ├── 机器学习-006：DeepLN之CNN源码.md ├── 机器学习-007：MachineLN之激活函数.md ├── 机器学习-008：DeepLN之BN.md ├── 机器学习-009：MachineLN之数据归一化.md ├── 机器学习-010：MachineLN之样本不均衡.md ├── 机器学习-011：MachineLN之过拟合.md ├── 机器学习-012：MachineLN之优化算法.md ├── 机器学习-013：MachineLN之kNN.md ├── 机器学习-014：MachineLN之kNN源码.md ├── 机器学习-015：MachineLN之感知机.md ├── 机器学习-016：MachineLN之感知机源码.md ├── 机器学习-017：MachineLN之逻辑回归.md ├── 机器学习-018：MachineLN之逻辑回归源码.md ├── 机器学习-019：MachineLN之SVM（1）.md ├── 机器学习-020：MachineLN之SVM（2）.md ├── 机器学习-021：MachineLN之SVM源码.md └── 机器学习-022：MachineLN之RL.md ├── README.md ├── TensorFlow-Tutorials ├── 00_multiply.ipynb ├── 00_multiply.py ├── 01_linear_regression.ipynb ├── 01_linear_regression.py ├── 02_logistic_regression.ipynb ├── 02_logistic_regression.py ├── 03_net.ipynb ├── 03_net.py ├── 04_modern_net.ipynb ├── 04_modern_net.py ├── 05_convolutional_net.ipynb ├── 05_convolutional_net.py ├── 06_autoencoder.ipynb ├── 06_autoencoder.py ├── 07_lstm.ipynb ├── 07_lstm.py ├── 08_word2vec.ipynb ├── 08_word2vec.py ├── 09_tensorboard.ipynb ├── 09_tensorboard.py ├── 10_save_restore_net.ipynb ├── 10_save_restore_net.py ├── 11_gan.ipynb ├── 11_gan.py └── README.md ├── Tensorflow-estimator-classification ├── 00_mnist.py ├── 01_map.png ├── 01_pascal.py ├── 02_pascal_alexnet.py ├── 03_pascal_vgg.py ├── 04_pascal_vgg_finetune.py ├── 05_alexnet_conv1.py ├── 05_alexnet_eval.py ├── 05_alexnet_nn.py ├── 05_vgg_eval.py ├── 05_vgg_nn.py ├── 05_vgg_tsne.py ├── 06_pascal_alexnet_mixup.py ├── MNIST-data │ ├── README.md │ ├── t10k-images-idx3-ubyte.gz │ ├── t10k-labels-idx1-ubyte.gz │ ├── train-images-idx3-ubyte.gz │ └── train-labels-idx1-ubyte.gz ├── README.md ├── eval.py ├── gpu_conf.sh ├── pascal_alexnet_mixup.png ├── pascal_vgg.png └── pascal_vgg_finetune.png ├── Tensorflow ├── 3_2_HelloWorld.py ├── 4_2_AutoEncoer.py ├── 4_4_MLP.py ├── 5_2_CNN_MNIST.py ├── 5_3_CNN_CIFAR10.py ├── 6_1_AlexNet.py ├── 6_2_VGG.py ├── 6_3_InceptionNet.py ├── 6_4_ResNet.py ├── 7_1_Word2Vec.py ├── 7_2_LSTM.py ├── 7_3_BiRNN.py ├── 8_2_PolicyNetwork.py ├── 8_3_GridWorld.py ├── 8_3_Value_Network.py ├── 9_1_TensorBoard.py ├── 9_2_MultiGPU.py ├── 9_3_Distributed.py ├── README.md └── Tensorflow and Word2vec.txt ├── face_detection ├── README.md ├── 人脸检测——AFLW准备人脸.md ├── 人脸检测——fcn.md ├── 人脸检测——mtcnn思想，生成negative、positive、part样本。.md ├── 人脸检测——准备非人脸.md ├── 人脸检测——滑动窗口篇（训练和实现）.md ├── 人脸检测——生成矫正人脸——cascade-cnn的思想，-但是mtcnn的效果貌似更赞.md └── 人脸检测——矫正人脸生成标签.md ├── ml_in_action ├── Perceptron.py ├── README.md ├── bayes.py ├── kNN.py ├── logRegres.py ├── svmMLiA.py ├── treePlotter.py └── trees.py ├── tensorflow_in_action ├── README.md ├── 学习笔记TF001_ 什么是TensorFlow.md ├── 学习笔记TF002_ 怎么安装TensorFlow.md ├── 学习笔记TF003_数据流图定义、执行、可视化.md ├── 学习笔记TF004_张量表示、类型、形状、计算.md ├── 学习笔记TF005_Graph对象、Session对象、占位符.md ├── 学习笔记TF006_Variable对象、名称作用域.md ├── 学习笔记TF007_Tensor、Graph、Op、Variable、占位符、Session、名称作用域、Board综合例子.md ├── 学习笔记TF008_机器学习基础 线性回归.md ├── 学习笔记TF009_对数几率回归.md ├── 学习笔记TF010_softmax分类.md ├── 学习笔记TF011_多层神经网络.md ├── 学习笔记TF012_卷积网络简述.md ├── 学习笔记TF013_卷积、跨度、边界填充、卷积核.md ├── 学习笔记TF014_卷积层、激活函数、池化层、归一化层、高级层.md ├── 学习笔记TF015_加载图像、图像格式、图像操作、颜色.md ├── 学习笔记TF016_CNN实现、数据集、TFRecord、加载图像、模型、训练、调试.md ├── 学习笔记TF017_自然语言处理、RNN、LSTM.md ├── 学习笔记TF018_词向量、维基百科语料库训练词向量模型.md ├── 学习笔记TF019_序列分类、IMDB影评分类.md ├── 学习笔记TF020_序列标注、手写小写字母OCR数据集、双向RNN.md ├── 学习笔记TF021_预测编码、字符级语言建模、ArXiv摘要.md ├── 学习笔记TF022_产品环境模型部署、Docker镜像、Bazel工作区、导出模型、服务器、客户端.md ├── 学习笔记TF023_下载、缓存、属性字典、惰性属性、覆盖数据流图、资源.md ├── 学习笔记TF024_TensorFlow实现Softmax Regression(回归)识别手写数字.md ├── 学习笔记TF025_自编码器.md ├── 学习笔记TF026_多层感知机.md ├── 学习笔记TF027_卷积神经网络.md ├── 学习笔记TF028_实现简单卷积网络.md ├── 学习笔记TF029_实现进阶卷积网络.md ├── 学习笔记TF030_实现AlexNet.md ├── 学习笔记TF031_实现VGGNet.md ├── 学习笔记TF032_实现Google Inception Net.md ├── 学习笔记TF033_实现ResNet.md ├── 学习笔记TF034_实现Word2Vec.md ├── 学习笔记TF035_实现基于LSTM语言模型.md ├── 学习笔记TF036_实现Bidirectional LSTM Classifier.md ├── 学习笔记TF037_实现强化学习策略网络.md ├── 学习笔记TF038_实现估值网络.md ├── 学习笔记TF039_TensorBoard.md ├── 学习笔记TF040_多GPU并行.md ├── 学习笔记TF041_分布式并行.md ├── 学习笔记TF042_TF.Learn、分布式Estimator、深度学习Estimator.md ├── 学习笔记TF043_TF.Learn 机器学习Estimator、DataFrame、监督器Monitors.md ├── 学习笔记TF044_TF.Contrib组件、统计分布、Layer、性能分析器tfprof.md ├── 学习笔记TF045_人工智能、深度学习、TensorFlow、比赛、公司.md ├── 学习笔记TF046_TensoFlow开发环境，Mac、Ubuntu、Linux、Windows，CPU版本、GPU版本.md ├── 学习笔记TF047_PlayGround、TensorBoard.md ├── 学习笔记TF048_TensorFlow 系统架构、设计理念、编程模型、API、作用域、批标准化、神经元函数优化.md ├── 学习笔记TF049_TensorFlow 模型存储加载、队列线程、加载数据、自定义操作.md ├── 学习笔记TF050_TensorFlow源代码解析.md └── 学习笔记TF051_生成式对抗网络.md └── tf-API ├── README.md ├── tf-API-研读1：tf-nn，tf-layers，-tf-contrib概述.md ├── tf-API-研读2：math.md └── tf-API-研读3：Building-Graphs.md /MachinLN/README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MachineLP/Tensorflow-/HEAD/MachinLN/README.md 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