Pinned Repositories
seanv507's Repositories
seanv507/liblinear_weights
seanv507/aas
Code to accompany Advanced Analytics with Spark from O'Reilly Media
seanv507/caffe
Caffe: a fast open framework for deep learning.
seanv507/code
Code of Amazon Web Services in Action
seanv507/coursera_scala
seanv507/coursera_scala_spark_timeusage
seanv507/coursera_spark
seanv507/crea
seanv507/cyvlfeat
A thin Cython wrapper around select areas of vlfeat
seanv507/deep_learning_udacity
seanv507/Demo-Tapster
seanv507/dryworkflow
DRY (Don't Repeat Yourself) Workflow for more efficient data analysis using R
seanv507/glmnet
:exclamation: This is a read-only mirror of the CRAN R package repository. glmnet — Lasso and Elastic-Net Regularized Generalized Linear Models. Homepage: http://www.jstatsoft.org/v33/i01/.
seanv507/glmnetUtils
Utilities for glmnet
seanv507/liblinear
seanv507/LiblineaR-1
:exclamation: This is a read-only mirror of the CRAN R package repository. LiblineaR — Linear Predictive Models Based on the 'LIBLINEAR' C/C++ Library. Homepage: http://dnalytics.com/liblinear/
seanv507/movies
seanv507/MSD_sparse
seanv507/pivottable
Javascript Pivot Table (aka Pivot Grid, Pivot Chart, Cross-Tab) implementation with drag'n'drop.
seanv507/practical-object-category-recognition
A VGG practical on object category recognition.
seanv507/r-gitgnore
.gitignore file(s) specifying R and Rmarkdown related files and patterns not to be tracked by git
seanv507/r-makefile-definitions
R related Makefile definitions
seanv507/rdds-dataframes-datasets-presentation-2016
Source for "RDDs, DataFrames and Datasets in Apache Spark" NEScala presentation
seanv507/survival
:exclamation: This is a read-only mirror of the CRAN R package repository. survival — Survival Analysis
seanv507/tensorflow
Computation using data flow graphs for scalable machine learning
seanv507/tensorflow_work
seanv507/tests
seanv507/universal-recommender
Highly configurable recommender based on PredictionIO and Mahout's Correlated Cross-Occurrence algorithm
seanv507/user2016-talk
Peter's talk at UseR! 2016, Wednesday 1:36pm, Stanford: GNU make for reproducible data analysis using R and other statistical software
seanv507/vlfeat
An open library of computer vision algorithms