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Themes and Conferences per Pacoid, Episode 2

Paco Nathan's column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI and Economics. Introduction Welcome back to...

Trust in LIME: Yes, No, Maybe So? 

In this Domino Data Science Field Note, we briefly discuss an algorithm and framework for generating explanations, LIME (Local Interpretable Model-Agnostic Explanations), that may help data...

Themes and Conferences per Pacoid, Episode 1

Introduction: New Monthly Series! Welcome to a new monthly series! I’ll summarize highlights from recent industry conferences, new open source projects, interesting research, great examples, amazing...

Docker, but for Data

Aneesh Karve, Co-founder and CTO of Quilt, visited the Domino MeetUp to discuss the evolution of data infrastructure. This blog post provides a session summary, video,...

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...

Humans in the Loop

This guest blog post from Paco Nathan dives into how people and machines collaborating together to perform work is real and not science fiction. Paco Nathan is...

New G3 Instances in AWS – Worth it for Machine Learning?

We benchmarked AWS’s new G3 instances for deep learning tasks and found they significantly outperform the older P2 instances. The new G3 instances are now available...

Data Science != Software Engineering

Domino’s guide, “What Engineering Leaders Need to Know About Data Science”, provides insights to help engineering leaders increase data science productivity and decrease engineering time spent...

Model Deployment Powered by Kubernetes

In this article we explain how we’re using Kubernetes to enable data scientists to deploy predictive models as production-grade APIs. Background Domino lets users publish R...

Data Science on AWS: Benefits and Common Pitfalls

More than two years ago, we wrote about the misguided fear of the cloud among many enterprise companies. How quickly things change! Today, every enterprise we...

Deep Learning on GPUs without the Environment Setup

We have seen an explosion of interest among data scientists who want to use GPUs for training deep learning models. While the libraries to support this...

Enabling Data Science Agility with Docker

This post describes how Domino uses Docker to solve a number of interconnected problems for data scientists and researchers, related to environment agility and reproducibility of...

Image diffing with CSS tricks

We've been hard at work delivering exciting new features in Domino. Our latest release included a lot, including the ability to import/share data sets across projects,...