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Commits on Sep 7, 2017

• USD-INR Exchange Rate Data

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Commits on Jun 14, 2017

• Logistic_Regression(Keras, Confusion, R2, K-Fold)

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Commits on May 10, 2017

• Early Stopping Monitor

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• Comparing 2 Different Deep Neural Networks

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• Delete model1_vs_model1_plotting.py

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• 3 different models comparison based on Validation Loss

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• MNIST classification using deep networks

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• MNIST classification using deep networks

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Commits on May 9, 2017

• 3 different models comparison based on Validation Loss

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• 3 different models comparison based on Validation Loss

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• Early Stopping Monitor

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• Stochastic Gradient Descent Optimizer

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• Comparing 2 Different Deep Neural Networks

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Commits on May 8, 2017

• A Deep Two Layer Classification Using Keras-NN on Titanic Data

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Commits on May 7, 2017

• Classification Using Keras-NN on Titanic Data

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• Delete Classification_Using_keras.py

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• Update Classification_Using_keras.py

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• Prediction on Titanic Data

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• Titanic Data

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• Delete Regression_using_Keras.py

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• Using Keras develop a model for Regression. Dataset is the Current Population Survey

  

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• Current Population Survey Dataset

  

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• Current Population Survey Dataset

  

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• Using Keras develop a model for Regression. Dataset is the Current Population Survey

  

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Commits on May 6, 2017

• Testing phase

  

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Commits on May 3, 2017

• Mean squared error regression loss

  

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• Multiple layers of computational units, interconnected in a feed-forward way

  

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• Using Gradient Descent to find Local Minima

  

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• remove Multi-layer_Neural_Networks.py

  

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• Using Gradient Descent to Find Local Minima

  

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• Code to do forward propagation for a neural network with 2 hidden layers. Each hidden layer has two nodes.

  

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• A Simple Feed Forward Neural Network with ReLU Activation Function

  

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• A Simple Feed Forward Neural Network with ReLU Activation Function

  

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• Initial Commit

  

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• Initial commit

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