Setting up the environment for kaggle

Dependencies for deep learning environments

Python base image on ubuntu 16.04 operating system with cpu and gpu support

These images are for CPU and GPU based environment management over ubuntu operating system (16.04)

Environment for mxnet library

With environment for opencv, sklearn, xgboost

keras with tensorflow backend

pytorch intallation on ubuntu 14.04

Image with sklearn, xgboost etc. mostly used during data science processes

Environment for R programming language for data science

Rstudio + ubuntu image

Environment for caffe2

Prerequisite for datmo CLI with ubuntu

Integration with datadotworld along with scipy, pandas, sklearn and xgboost libraries

Image with sklearn, numpy, scipy and catboost for numerical data science problems

Image with sklearn, numpy, scipy and xgboost for numerical data science problems

dlib and scikit-learn installation on ubuntu

keras installed with theano backend

basic theano installation on ubuntu 14.04

automatically build tensorflow images from github

spacy installation