{"id":13435161,"url":"https://github.com/YunYang1994/TensorFlow2.0-Examples","last_synced_at":"2025-03-18T02:31:11.302Z","repository":{"id":35840432,"uuid":"174368811","full_name":"YunYang1994/TensorFlow2.0-Examples","owner":"YunYang1994","description":"🙄 Difficult algorithm, Simple code.","archived":false,"fork":false,"pushed_at":"2023-03-25T00:21:23.000Z","size":10630,"stargazers_count":1713,"open_issues_count":105,"forks_count":676,"subscribers_count":58,"default_branch":"master","last_synced_at":"2024-10-17T13:14:32.234Z","etag":null,"topics":["convolutional-neural-network","dcgan-tensorflow","deep-learning","deep-neural-networks","fcn8s","gan","image-classification","linear-regression","machine-learning","object-detection","pix2pix","reinforcement-learning","resnet","tensorflow","tensorflow-examples","tensorflow2","unet-image-segmentation","vgg16","yolov3"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","readme":"\u003ch2 align=\"center\"\u003e\u003ccode\u003e🎉TensorFlow2.0-Examples🎉!\u003c/code\u003e\u003c/h2\u003e\n\u003cp align=\"center\"\u003e\"\u003ci\u003eTalk is cheap, show me the code.\u003c/i\u003e\" \n  ----- Linus Torvalds\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Branch-master-green.svg?longCache=true\"\n        alt=\"Branch\"\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/YunYang1994/TensorFlow2.0-Examples/stargazers\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/stars/YunYang1994/TensorFlow2.0-Examples.svg?label=Stars\u0026style=social\"\n        alt=\"Stars\"\u003e\n  \u003c/a\u003e\n    \u003ca href=\"https://github.com/YunYang1994/TensorFlow2.0-Examples/network/members\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/forks/YunYang1994/TensorFlow2.0-Examples.svg?label=Forks\u0026style=social\"\n        alt=\"Forks\"\u003e\n  \u003c/a\u003e\n  \u003c/a\u003e\n   \u003ca href=\"https://github.com/sindresorhus/awesome\"\u003e\n   \u003cimg src=\"https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg\"\n        alt=\"Awesome\"\u003e\n  \u003c/a\u003e\n  \u003c/a\u003e\n   \u003ca href=\"https://github.com/YunYang1994/TensorFlow2.0-Examples/blob/master/LICENSE\"\u003e\n   \u003cimg src=\"https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000\"\n        alt=\"Awesome\"\u003e\n\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n  \u003csub\u003eCreated by\n  \u003ca href=\"https://github.com/YunYang1994\"\u003eYunYang1994\u003c/a\u003e\n\u003c/div\u003e\n\u003cbr\u003e\n    \nThis tutorial was designed for easily diving into TensorFlow2.0.  it includes both notebooks and source codes with explanation. **It will be continuously updated !** 🐍🐍🐍🐍🐍🐍\n\n## Contents\n\n#### 1 - Introduction\n- **Hello World** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/helloworld.ipynb)) ([code](1-Introduction/helloworld.py)). Very simple example to learn how to print \"hello world\" using TensorFlow.\n- **Variable** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/variable.ipynb)) ([code](1-Introduction/variable.py)). Learn to use variable in tensorflow.\n- **Basical operation** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/basic_operations.ipynb)) ([code](1-Introduction/basic_operations.py)). A simple example that covers TensorFlow basic operations.\n- **Activation** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/activation.ipynb)) ([code](1-Introduction/activation.py)). Start to know some activation functions in tensorflow.\n- **GradientTape** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/GradientTape.ipynb)) ([code](1-Introduction/GradientTape.py)). Introduce a key technique for automatic differentiation\n\n#### 2 - Basical Models\n- **Linear Regression** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/2-Basical_Models/Linear_Regression.ipynb)) ([code](2-Basical_Models/Linear_Regression.py)). Implement a Linear Regression with TensorFlow.\n- **Logistic Regression** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/2-Basical_Models/Logistic_Regression.ipynb)) ([code](2-Basical_Models/Logistic_Regression.py)). Implement a Logistic Regression with TensorFlow.\n- **Multilayer Perceptron Layer** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/2-Basical_Models/Multilayer_Perceptron.ipynb)) ([code](2-Basical_Models/Multilayer_Perceptron.py)). Implement Multi-Layer Perceptron Model with TensorFlow.\n- **CNN** ([notebook](https://tensorflow.google.cn/tutorials/quickstart/advanced)) ([code](2-Basical_Models/CNN.py)). Implement CNN Model with TensorFlow. \n\n#### 3 - Neural Network Architecture\n- **VGG16** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture/vgg16.py))([paper](https://arxiv.org/pdf/1409.1556.pdf)). VGG16: Very Deep Convolutional Networks for Large-Scale Image Recognition. \n- **Resnet** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture/resnet.py))([paper](https://arxiv.org/pdf/1512.03385.pdf)). Resnet: Deep Residual Learning for Image Recognition. 🔥🔥🔥\n- **AutoEncoder** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture/autoencoder.py))([paper](http://www.cs.toronto.edu/~hinton/science.pdf)). AutoEncoder: Reducing the Dimensionality of Data with Neural Networks.\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"65%\" src=\"https://user-images.githubusercontent.com/30433053/68206851-b08d2580-0008-11ea-8b51-061e0cbead62.gif\" style=\"max-width:65%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n- **FPN** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Neural_Network_Architecture/fpn.py))([paper](https://arxiv.org/abs/1612.03144)). FPN: Feature Pyramid Networks for Object Detection. \n\n#### 4 - Object Detection\n- **RPN** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/RPN)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/RPN/rpn.py))([paper](https://arxiv.org/pdf/1703.06283.pdf)). RPN:  a Region Proposal Network 🔥🔥🔥🔥🔥\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"70%\" src=\"https://user-images.githubusercontent.com/30433053/67913231-4e2ac400-fbc7-11e9-9995-94ed6f7181d4.png\" style=\"max-width:70%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n- **MTCNN** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/MTCNN)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/MTCNN/mtcnn.py))([paper](https://arxiv.org/abs/1604.02878)). MTCNN: Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks. *(Face detection and Alignment)* 🔥🔥\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"40%\" src=\"https://user-images.githubusercontent.com/30433053/68547531-7e6f2f80-041d-11ea-8cfb-0c5a22af0921.jpg\" style=\"max-width:40%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n- **YOLOv3** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/YOLOV3)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/YOLOV3/core/yolov3.py))([paper](https://arxiv.org/pdf/1804.02767.pdf)). YOLOv3: An Incremental Improvement.🔥🔥🔥🔥\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"65%\" src=\"https://user-images.githubusercontent.com/30433053/67914531-656bb080-fbcb-11e9-9775-302a25faf747.png\" style=\"max-width:65%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n- **SSD** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/SSD)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/SSD/ssd.py))([paper](http://arxiv.org/abs/1512.02325)). SSD: Single Shot MultiBox Detector.🔥🔥🔥🔥 【TO DO】\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"56%\" src=\"https://user-images.githubusercontent.com/30433053/68290134-5f416c80-00c2-11ea-8cbc-d6010ced4efd.png\" style=\"max-width:56%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n- **Faster R-CNN** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/Faster-RCNN)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/Faster-RCNN/frcnn.py))([paper](http://arxiv.org/abs/1506.01497)). Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.🔥🔥🔥🔥 【TO DO】\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"65%\" src=\"https://user-images.githubusercontent.com/30433053/68546623-54187480-0413-11ea-9396-0a698c5a2580.png\" style=\"max-width:65%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n#### 5 - Image Segmentation\n- **FCN** ([notebook](5-Image_Segmentation/FCN)) ([code](5-Image_Segmentation/FCN/fcn8s.py))([paper](https://arxiv.org/abs/1411.4038)). FCN: Fully Convolutional Networks for Semantic Segmentation. 🔥🔥🔥🔥🔥\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"60%\" src=\"https://user-images.githubusercontent.com/30433053/67917411-e62eaa80-fbd3-11e9-9fe1-95550cf559d7.png\" style=\"max-width:60%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n- **Unet** ([notebook](5-Image_Segmentation/Unet)) ([code](5-Image_Segmentation/Unet/train.py))([paper](https://arxiv.org/abs/1505.04597)). U-Net: Convolutional Networks for Biomedical Image Segmentation. 🔥🔥\n\n\u003cp align=\"center\"\u003e\n    \u003cimg width=\"50%\" src=\"https://user-images.githubusercontent.com/30433053/67922238-2ba7a380-fbe5-11e9-96a0-55c6827bd024.png\" style=\"max-width:50%;\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n#### 6 - Generative Adversarial Networks\n- **DCGAN** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/6-Generative_Adversarial_Networks/dcgan.ipynb)) ([code](6-Generative_Adversarial_Networks/dcgan.py))([paper](https://arxiv.org/pdf/1511.06434.pdf)).  Deep Convolutional Generative Adversarial Network.\n- **Pix2Pix** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/6-Generative_Adversarial_Networks/Pix2Pix.ipynb)) ([code](6-Generative_Adversarial_Networks/Pix2Pix.py))([paper](https://arxiv.org/pdf/1611.07004.pdf)).  Image-to-Image Translation with Conditional Adversarial Networks.\n\n#### 7 - Utils\n- **Multiple GPU Training** ([notebook](https://yunyang1994.github.io/posts/TensorFlow-的多卡-GPU-训练机制/#more))([code](7-Utils/multi_gpu_train.py)). Use multiple GPU to train your model.\n","funding_links":["https://github.com/YunYang1994/TensorFlow2.0-Examples/blob/master/.github/Sponsor.md"],"categories":["Jupyter Notebook","框架学习资料汇总","Sample Codes / Projects \u003ca name=\"sample\" /\u003e ⛏️📐📁","Tutorials 💛💛💛💛💛\u003ca name=\"github-tutorials\" /\u003e"],"sub_categories":["General 🚧 \u003ca name=\"GeneralCode\" /\u003e"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FYunYang1994%2FTensorFlow2.0-Examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FYunYang1994%2FTensorFlow2.0-Examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FYunYang1994%2FTensorFlow2.0-Examples/lists"}