Tag: Python
On the Importance of Community-Led Open Source
Wes McKinney, Director of Ursa Labs and creator of pandas project, presented the keynote, "Advancing Data Science Through Open Source" at Rev. McKinney's keynote covered open...
Building a Domino Web App with Dash
Randi R. Ludwig, Data Scientist at Dell EMC and an organizer of Women in Data Science ATX, covers how to build a Domino web app with...
Intel’s Python Distribution is Smoking Fast, and Now it’s in Domino
Domino just finished benchmarking Intel’s Python Distribution, and it is fast, very fast. Intel’s Python distribution is available for use in Domino. Intel’s Python Distribution People...
Reproducible Machine Learning with Jupyter and Quilt
In this guest blog post, Aneesh Karve, Co-founder and CTO of Quilt, demonstrates how Quilt works in conjunction with Domino's Reproducibility Engine to make Jupyter notebooks...
Reproducible Dashboards and Other Great Things to do with Jupyter
Mac Rogers, Research Engineer at Domino, presented best practices for creating Jupyter dashboards at a recent Domino Data Science Pop-Up. Session Summary In this Data Science...
Horizontal Scaling for Parallel Experimentation
The amount of time data scientists spend waiting for experiment results is the difference between making incremental improvements and making significant advances. With parallel experimentation, data...
Multicore Data Science with R and Python
This article is an excerpt from the full video on Multicore Data Science in R and Python. Watch the full video to learn how to leverage...
Imbalanced Datasets
Imagine you are a medical professional who is training a classifier to detect whether an individual has an extremely rare disease. You train your classifier, and...
Fitting Gaussian Process Models in Python
Written by Chris Fonnesbeck, Assistant Professor of Biostatistics, Vanderbilt University Medical Center. You can view, fork, and play with this project on the Domino data science...
Achieving Reproducibility with Conda and Domino Environments
Managing “environments” (i.e., the set of packages, configuration, etc.) is a critical capability of any Data Science Platform. Not only does environment setup waste time on-boarding...
Python 3.6 with Domino in Minutes
For Pythonistas like me, the holidays started a little early with today's release of Python 3.6. In case you haven't heard, Python 3.6 has a number...
Python for SAS Users: The pandas Data Analysis Library
Ths post is a chapter from Randy Betancourt's Python for SAS Users quick start guide. Randy wrote this guide to familiarize SAS users with Python and...
R vs. Python for Data Science
While the elections are over, some debates continue. R and Python are both popular programming languages for data scientists. Each has its advantages for performing data...