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Notebook","funding_links":[],"categories":["Jupyter Notebook"],"sub_categories":[],"readme":"# Advanced TensorFlow\nCollection of (Little More + Refactored) Advanced TensorFlow Implementations. \nTry my best to implement algorithms with a single Jupyter Notebook. \n\n### [AutoEncoder](https://github.com/sjchoi86/advanced-tensorflow/tree/master/ae)\n- Denoising AutoEncoder\n- Convolutional AutoEncoder (using deconvolution)\n- Variational AutoEncoder\n### [Adversarial Variational Bayes](https://github.com/sjchoi86/advanced-tensorflow/tree/master/avb)\n- AVB on 2-dimensional Toy Example\n### [Basics](https://github.com/sjchoi86/advanced-tensorflow/tree/master/basic)\n- Basic Classification (MLP and CNN)\n- Custom Dataset Generation\n- Classification (MLP and CNN) using Custom Dataset\n- OOP Style Implementation of MLP and CNN\n### [Class Activation Map](https://github.com/sjchoi86/advanced-tensorflow/tree/master/cam)\n- Pretrained Network Usage with TF-SLIM\n- Class Activation Map with Pretrained Network\n### [Char-RNN](https://github.com/sjchoi86/advanced-tensorflow/tree/master/char-rnn)\n- Preprocess Linux Kernel Sources\n- Train and Sample with Char-RNN\n### [Domain Adaptation](https://github.com/sjchoi86/advanced-tensorflow/tree/master/dann)\n- Domain Adversarial Neural Network with Gradient Reversal Layer\n### [Generative Adversarial Network](https://github.com/sjchoi86/advanced-tensorflow/tree/master/dcgan)\n- Deep Convolutional Generative Adversarial Network with MNIST \n### [Mixture Density Network](https://github.com/sjchoi86/advanced-tensorflow/tree/master/mdn)\n- Mixture Density Network\n- Heteroscedastic Mixture Density Network\n### [Reinforcement Learning](https://github.com/sjchoi86/advanced-tensorflow/tree/master/rl)\n- Model Based RL (Value Iteration and Policy Iteration)\n### [TF-SLIM](https://github.com/sjchoi86/advanced-tensorflow/tree/master/mnist)\n- MNIST Classification with TF-SLIM\n### [Super Resolution](https://github.com/sjchoi86/advanced-tensorflow/tree/master/srgan)\n- Super-resolution with Generative Adversarial Network\n\n## Requirements\n- Python-2.7\n- TensorFlow-1.0.1\n- SciPy\n- MatplotLib\n- Jupyter Notebook\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsjchoi86%2Fadvanced-tensorflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsjchoi86%2Fadvanced-tensorflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsjchoi86%2Fadvanced-tensorflow/lists"}