philmar1

Multiscale_PHATE

Creating multi-resolution embeddings and clusters from high dimensional data

Deep-Dreams-and-Adversarial-Examples

School lab, testing Deep Dreams and Adversarial Examples with CNN

GAIN

Generative Adversarial Imputation Networks (GAIN)

Generating-Sebastian_Bach-Music-with-RNN

School lab, using many to many and one to many RNN

graphs_in_ml_mva

megan-own

Project aiming to test new features in MEGAN

Metaheuristic-for-Maximisation-of-the-Covarage-of-Radars

PIK3CA-mutation-prediction

Q-Learning-for-Pacman

School project based on the UC Berkeley CS188 course

Sentiment-Analysis-with-Naive-Bayes-and-RNN

philmar1/Deep-Dreams-and-Adversarial-Examples

School lab, testing Deep Dreams and Adversarial Examples with CNN

philmar1/GAIN

Generative Adversarial Imputation Networks (GAIN)

philmar1/Generating-Sebastian_Bach-Music-with-RNN

School lab, using many to many and one to many RNN

philmar1/graphs_in_ml_mva

philmar1/megan-own

Project aiming to test new features in MEGAN

philmar1/Metaheuristic-for-Maximisation-of-the-Covarage-of-Radars

philmar1/PIK3CA-mutation-prediction

philmar1/Q-Learning-for-Pacman

School project based on the UC Berkeley CS188 course

philmar1/Sentiment-Analysis-with-Naive-Bayes-and-RNN

philmar1/Signals-Convolution-with-GPU-and-CUDA

School project, using GPU programming to speed up convolutions