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:
https://github.com/stephencwelch/Neur...

Nate Silver's Book: http://www.amazon.com/Signal-Noise-Ma...

Caltech Machine Learning Course: https://work.caltech.edu/telecourse.html

And the lecture shown: Lecture 07 - The VC Dimension

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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