Tag: Data Science

Reflections on the Data Science Platform Market

Reflections Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the...

Model Interpretability with TCAV (Testing with Concept Activation Vectors)

This Domino Data Science Field Note provides very distilled insights and excerpts from Been Kim’s recent MLConf 2018 talk and research about Testing with Concept Activation Vectors...

Themes and Conferences per Pacoid, Episode 5

In Paco Nathan's latest column, he explores the theme of "learning data science" by diving into education programs, learning materials, educational approaches, as well as perceptions...

Data Science vs Engineering: Tension Points

This blog post provides highlights and a full written transcript from the panel, “Data Science Versus Engineering: Does It Really Have To Be This Way?” with...

Collaboration Between Data Science and Data Engineering: True or False?

This blog post includes candid insights about addressing tension points that arise when people collaborate on developing and deploying models. Domino’s Head of Content sat down...

The Past/Present/Future + Myths of Data Science

Sivan Aldor-Noiman, VP of Data Science at Wellio, presented “The Past/Present/Future + Myths of Data Science” at Domino. This blog post provides a few highlights from...

Avoiding a Data Science Hype Bubble

In this post, Josh Poduska, Chief Data Scientist at Domino Data Lab, advocates for a common taxonomy of terms within the data science industry. The proposed...

Fuzzy Matching to the Rescue

Jennifer Shin is the Founder & Chief Data Scientist at 8 Path Solutions. Jennifer is on the faculty in the data science graduate program at UC Berkeley, on the...

Stakeholder-Driven Data Science at Warby Parker

Max Shron, the head of data science at Warby Parker, delivered a presentation on stakeholder-driven data science at a Data Science Popup. This blog post provides a...

Answering Questions About Model Delivery on AWS at Strata

This post is a recap of the common questions Domino answered in the booth at Strata New York. We answered questions about access to EC2 machines,...

What Your CIO Needs to Know about Data Science

What would you rather be doing? Data science or DevOps? As a data scientist, your CIO may hear from you that model deployment is a challenge...

Domino for Good: Collaboration, Reproducibility, and Openness, in the Service of Societal Benefit

The Path of a Data Do-Gooder When I joined Domino Data Lab to lead the Domino for Good initiative a few months ago, it felt like the...

Domino now supports JupyterLab — and so much more

You can now run JupyterLab in Domino, using a new Domino feature that lets data scientists specify any web-based tools they want to run on top...