Conv Nets II
In this project we automate learning CNN hyper-params. We test and improve my previous tensorflow implementation of CNN in here on Kaggle's facial expression dataset. Here I only deal with two label classes: Happy and Angry. Randomized Search for learning hyper_paramters such as learning_rate, momentum coefficient, etc and drop-out regularizer improved the default test prediction accuracy from 36% to 64%. This is a bit lower than 72% that we got from our SVM classifier. However, we will continue in following projects to see if we can beat...