- lxml - Pythonic binding for the C libraries libxml2 and libxslt.
- boto - Python interface to Amazon Web Services
- Django - Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
- Fabric - Library and command-line tool for streamlining the use of SSH for application deployment or systems administration task.
- PyMongo - Tools for working with MongoDB, and is the recommended way to work with MongoDB from Python.
- Celery - Task queue to distribute work across threads or machines.
- pytz - pytz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.4 or higher.
MdKuasha
MdKuasha
/ h2o_xgboost_grid_example.R
Created
July 25, 2018 23:48
— forked from ledell/h2o_xgboost_grid_example.R
Demo of how to use grid search on H2O's XGBoost: http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/xgboost.html
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| library(h2o) | |
| h2o.init() | |
| # Load the HIGGS dataset | |
| train <- h2o.importFile("https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv") | |
| test <- h2o.importFile("https://s3.amazonaws.com/erin-data/higgs/higgs_test_5k.csv") | |
| y <- "response" | |
| x <- setdiff(names(train), y) | |
| family <- "binomial" |
MdKuasha
/ h2o_xgboost_grid_example.R
Created
July 25, 2018 23:48
— forked from ledell/h2o_xgboost_grid_example.R
Demo of how to use grid search on H2O's XGBoost: http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/xgboost.html
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| library(h2o) | |
| h2o.init() | |
| # Load the HIGGS dataset | |
| train <- h2o.importFile("https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv") | |
| test <- h2o.importFile("https://s3.amazonaws.com/erin-data/higgs/higgs_test_5k.csv") | |
| y <- "response" | |
| x <- setdiff(names(train), y) | |
| family <- "binomial" |
MdKuasha
/ python_resources.md
Created
July 19, 2018 19:50
— forked from krishnanalluri/python_resources.md
Python-related modules and guides.