A DATAML200 - Pattern Recognition and Machine learning Course Repository

EX2 - Multi-layer Percepteron (MLP)

Ex2.py defines a Multi-layer percepteron in Keras, compiles and trains the network. EX2 Documentation

EX3 - Convolutional Neural Network(CNN)

Ex3.py defines a convolutional neural network in Keras, compiles and trains the network. EX3 Documentation

EX4 - Detector evaluation and autoencoder denoising

Detector evaluation (ROC Analysis)

ROC.py calculates and plots the ROC curve of true positive rate (recall) vs false positive rate with 1-precision, from the “detector groundtruth.dat” and “detector output.dat”. ROC analysis provides a systematic tool for quantifying the impact of variability among individuals' decision thresholds. ROC stands for ”Receiver Operating Characteristic”. Wikipedia

Autoencoder denoising (Noisy MNIST Fashion classification)

Mnist.py is an auto-encoder that trains the neural network to encode and decode noisy images and to report different values from our network.

EX4 Documentation