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

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: Nate Silver’s Book: =sr_1_1?ie=UTF8&qid=1421442340&sr=8-1&keywords=signal and the noise Caltech Machine Learning Course: And the lecture shown: 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