Pinned Repositories
2048
A small clone of 1024 (https://play.google.com/store/apps/details?id=com.veewo.a1024)
datasciencecoursera
datasciencecoursera
datasharing
The Leek group guide to data sharing
DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
dqn
An implementation of Deep Q-Network using Caffe
edX--6.00.1x-CompSci-2013
MITx: 6.00.1x Introduction to Computer Science and Programming. -- This repo is full of my solutions to the problems. Still new to CompSci / Python, feel free to suggest anything better if I'm doing something wrong.
principles-of-computing
My mini projects for the Principles of Computing Python Course.
Replicating-DeepMind
Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind
stanford_dl_ex
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial
slmjlf's Repositories
slmjlf/2048
A small clone of 1024 (https://play.google.com/store/apps/details?id=com.veewo.a1024)
slmjlf/datasciencecoursera
datasciencecoursera
slmjlf/datasharing
The Leek group guide to data sharing
slmjlf/DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
slmjlf/dqn
An implementation of Deep Q-Network using Caffe
slmjlf/edX--6.00.1x-CompSci-2013
MITx: 6.00.1x Introduction to Computer Science and Programming. -- This repo is full of my solutions to the problems. Still new to CompSci / Python, feel free to suggest anything better if I'm doing something wrong.
slmjlf/principles-of-computing
My mini projects for the Principles of Computing Python Course.
slmjlf/Replicating-DeepMind
Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind
slmjlf/stanford_dl_ex
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial