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...read more
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...read more
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...read more
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 PopUp. Session Summary In...read more
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...read more
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...read more
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...read more
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...read more
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...read more
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...read more
Python for SAS Users: The pandas Data Analysis Library
This post is a chapter from Randy Betancourt's Python for SAS Users quick start guide. Randy wrote this guide to familiarize SAS users...read more
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...read more
A Summary of Using k-NN in Production
This week, Domino’s Chief Data Scientist, Eduardo Ariño de la Rubia, presented a webinar: An Introduction to Using k-NN in Production. If you...read more
Join Us: An Introduction to Using k-NN in Production
Join us next Wednesday, October 5 for a webinar hosted by our Chief Data Scientist covering best practices for using k-NN in production....read more
Using Apache Spark to Analyze Large Neuroimaging Datasets
This article was written by Sergul Aydore, Ph.D., and Syed Ashrafulla, Ph.D. Sergul and Syed received their Ph.D.s in Electrical Engineering in 2014...read more
Announcing Enhanced Apache Spark Support
Domino now offers data scientists a simple, yet incredibly powerful way to conduct quantitative work using Apache Spark. Apache Spark has captured the...read more
Orchestrating Pipelines with Luigi and Domino
Building a data pipeline may sound like a daunting task. In this post, we will examine how you can use Luigi - a...read more
Using R and Python for Common SAS Functions
SAS is the recognized incumbent in the analytics, statistics and data science tool space. As the software celebrates its 50th birthday this year,...read more
Visualizing Machine Learning with Plotly and Domino
This post was contributed by Chelsea Douglas, a Software Engineer at Plotly. Want to play with the code from this post? Visit the...read more
Open Source Winning Against Proprietary Data Science Vendors
With the recent publication of Gartner’s Magic Quadrant for Advanced Analytics, we wanted to know how proprietary data science software vendors were faring...read more
Visual Logic Authoring vs Code
At some point in their careers, almost every data scientist has written code to perform a series of steps, and thought, “It would...read more
Python 3 Support in Jupyter
Domino lets you spin up Jupyter notebooks (and other interactive tools) with one click, on powerful cloud hardware. We recently added beta support...read more
Building Interactive Dashboards with Jupyter
Welcome to Part II of "Advanced Jupyter Notebook Tricks." In Part I, I described magics, and how to calculate notebooks in "batch" mode...read more
Advanced Jupyter Notebook Tricks — Part I
I love Jupyter notebooks! They're great for experimenting with new ideas or data sets, and although my notebook "playgrounds" start out as a...read more
Creating interactive crime maps with Folium
You can see this Domino project [here].(https://app.dominodatalab.com/u/r00sj3/crimemaps) I get very excited about a nice map. But when it comes to creating maps in...read more
Better interactive data science with Beaker and Rodeo
Domino has offered support for IPython/Jupyter for a while, but we recently added support for two newer, up-and-coming tools for interactive data science:...read more
Density-Based Clustering
Cluster Analysis is an important problem in data analysis. Data scientists use clustering to identify malfunctioning servers, group genes with similar expression patterns,...read more
To Jupyter and beyond
TLDR; Domino now supports Jupyter with R, Python, and Julia kernels as well as terminal access. It now renders ipynb files in the...read more
A/B Testing with Hierarchical Models in Python
In this post, I discuss a method for A/B testing using Beta-Binomial Hierarchical models to correct for a common pitfall when testing multiple...read more
Faster deep learning with GPUs and Theano
Domino recently added support for GPU instances. To celebrate this release, I will show you how to: Configure the Python library Theano to...read more