In this post I go through the algorithms presented in the groundbreaking AlphaGo Zero paper using pseudocode. The objective is to provide a high-level idea of what the model does. Why AlphaGo Zero matters Last week, Google DeepMind published their final iteration of AlphaGo, AlphaGo Zero. To say its performance is remarkable is an understatement. AlphaGo Zero made two breakthroughs: … Read More
Comparing model performance: Including Max Pooling and Dropout Layers
In this post I compare the performance of models that use max pooling and dropout in the convolutional layer with those that don’t. This experiment will be on a traffic sign classifier used in Udacity’s Self-Driving Car Nanodegree. The full code is on GitHub. Recap: Max Pooling and Dropout Max Pooling: A way of reducing the dimensionality of input (by … Read More