TensorFlow Basics Tutorial

Name		Name	Last commit message	Last commit date
Latest commit History 52 Commits
datasets		datasets
.gitignore		.gitignore
01. Tensorflow Basics.ipynb		01. Tensorflow Basics.ipynb
02. Tensorflow Graphs.ipynb		02. Tensorflow Graphs.ipynb
03. Simple Regression.ipynb		03. Simple Regression.ipynb
04. LinearRegressor and DNNClassifier (Estimator API).ipynb		04. LinearRegressor and DNNClassifier (Estimator API).ipynb
05. Regression using DNNRegressor.ipynb		05. Regression using DNNRegressor.ipynb
06. Classification using DNNClassifier.ipynb		06. Classification using DNNClassifier.ipynb
07. MNIST Using Vanilla Neural Nets.ipynb		07. MNIST Using Vanilla Neural Nets.ipynb
08. Convolutional Neural Nets (MNIST).ipynb		08. Convolutional Neural Nets (MNIST).ipynb
09. Convolutional Neural Networks (CIFAR-10).ipynb		09. Convolutional Neural Networks (CIFAR-10).ipynb
10. Recurrent Neural Network.ipynb		10. Recurrent Neural Network.ipynb
11. RNN for sin prediction.ipynb		11. RNN for sin prediction.ipynb
12. AutoEncoders.ipynb		12. AutoEncoders.ipynb
13. Generative Adverserial Networks.ipynb		13. Generative Adverserial Networks.ipynb
README.md		README.md

maykulkarni/tensorflow_tutorials