This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation.

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TensorFlow Examples

Code examples for some popular machine learning algorithms, using TensorFlow library. Both code and notebook are available.

Tutorial index

1 - Introduction

Hello World (notebook) (code)
Basic Operations (notebook) (code)

2 - Basic Classifiers

Nearest Neighbor (notebook) (code)
Linear Regression (notebook) (code)
Logistic Regression (notebook) (code)

3 - Neural Networks

Multilayer Perceptron (notebook) (code)
Convolutional Neural Network (notebook) (code)
AlexNet (notebook) (code)
Reccurent Network (code)

4 - Multi GPU

Basic Operations on multi-GPU (notebook) (code)

Dependencies

tensorflow
numpy
matplotlib
cuda (to run examples on GPU)

For more details about TensorFlow installation, you can check Setup_TensorFlow.md

Dataset

Some examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples (with input_data.py). MNIST is a database of handwritten digits, with 60,000 examples for training and 10,000 examples for testing. (Website: http://yann.lecun.com/exdb/mnist/)

Other tutorials are coming soon...

README.md