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Neural Networks Demystified [Part 7: Overfitting, Testing, and Regularization]

Duration: 05:53Views: 139.9KLikes: 4.1KDate Created: Jan, 2015

Channel: Welch Labs

Category: Travel & Events

Tags: computer science (field of study)overfittingartificial neural networksoftwaretechnology

Description: We've built and trained our neural network, but before we celebrate, we must be sure that our model is representative of the real world. Supporting Code: github.com/stephencwelch/Neural-Networks-Demystified Nate Silver's Book: amazon.com/Signal-Noise-Many-Predictions-Fail/dp/159420411X/ref=sr_1_1?ie=UTF8&qid=1421442340&sr=8-1&keywords=signal+and+the+noise Caltech Machine Learning Course: work.caltech.edu/telecourse.html And the lecture shown: youtu.be/Dc0sr0kdBVI?t=56m52s In this series, we will build and train a complete Artificial Neural Network in python. New videos every other friday. Part 1: Data + Architecture Part 2: Forward Propagation Part 3: Gradient Descent Part 4: Backpropagation Part 5: Numerical Gradient Checking Part 6: Training Part 7: Overfitting, Testing, and Regularization @stephencwelch welchlabs.com

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