berkeley-scf / gpu-workshop-2014Links
repository for materials for Chris Paciorek's workshop on GPU computation, April 2014
☆21Updated 11 years ago
Alternatives and similar repositories for gpu-workshop-2014
Users that are interested in gpu-workshop-2014 are comparing it to the libraries listed below
Sorting:
- A machine learning library focused on deep learning☆11Updated 10 years ago
- Notebooks containing R code from Richard McElreath's Statistical Rethinking☆71Updated 9 years ago
- akid is a python package written for doing research in Neural Network.☆14Updated 2 years ago
- Python package for inference with Gaussian processes☆11Updated 10 years ago
- A forest that is fast☆42Updated 6 years ago
- Jonker-Volgenant / LAPJV algorithm for the linear assignment problem, in Python☆52Updated 2 years ago
- ☆30Updated 5 years ago
- ☆16Updated 9 years ago
- Fork of cma-es library by Nikolaus Hansen☆12Updated 8 years ago
- Restricted Boltzmann Machines in R☆36Updated 5 years ago
- HAMSI (Hessian Approximated Multiple Subsets Iteration) is a parallel incremental optimization algorithm☆13Updated 5 years ago
- A quick educational implementation of a random forest classifier and a decsion jungle classifier.☆28Updated 10 years ago
- Lasagne / Theano tutorials for Nvidia Deep Learning Summercamp 2016☆26Updated 9 years ago
- Software for learning sparse Bayesian networks☆42Updated 5 years ago
- Simple structured learning framework for python☆38Updated 9 years ago
- Examples of building probabilistic models with MXNet linear algebra operators☆23Updated 8 years ago
- Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo☆52Updated 12 years ago
- Materials for the PyData San Francisco 2016 visualization tutorial☆14Updated 8 years ago
- An R package for large scale estimation with stochastic gradient descent☆62Updated last month
- An implementation of the SuperLearner algorithm in Python based on scikit-learn.☆25Updated 11 years ago
- ☆31Updated 9 years ago
- GURLS: a Least Squares Library for Supervised Learning☆62Updated 9 years ago
- Advanced workshop on XGBoost with Tianqi Chen in Santa Monica, June 2, 2016☆27Updated 9 years ago
- Deep exponential family models in MXNet/Gluon. Layers o' latents 💤☆17Updated 8 years ago
- Kohonen vector quantizers (SOM, NG, GNG)☆71Updated 7 years ago
- ☆10Updated 8 years ago
- Neighborhood Components Analysis in C++☆38Updated 15 years ago
- 2nd place submission to the MEG decoding competition https://www.kaggle.com/c/decoding-the-human-brain☆18Updated 11 years ago
- Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.☆16Updated 11 years ago
- Rectified Factor Networks☆37Updated 6 years ago