Curated Tensorflow code resources to help you get started with Deep Learning.

Each folder in this repo is named after a section of Deep Learning.

For example, the basics folder contains code to get you started with the syntax of Tensorflow (or TF). The projects folder contains real world predictions and classifications using TF.

Sometimes folders are also named with their respective algorithm names, like the regression and convolution_networks folders.

Start out with the hello_tensorflow.py file, then checkout the basics folder, work your way through basic_networks, costs_and_gradients, and finally regression and classification. By this time, you should be comfortable enough to work with other complicated resources in this repo.

• hello_tensorflow.py (simple beginner level introduction to Tensorflow.)

• basics (code resources to get familiar with the syntax of Tensorflow.)

• costs_and_gradients

  • hand_made_descent.py
  • plotting_cost.py

• basic_networks

  • basic_tf_network.py
  • basic_tf_with_hidden_network.py

• regression

  • linear_regression.py
  • logistic_regression.py

• classification

  • softmax_classification.py

• convolution_networks

  • Cifar10
  • MNIST

• projects

  • predicting_house_prices
  • predicting_onset_of_diabetes

This project is licensed under the MIT License - see the LICENSE file for details.

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