Latest

A Practitioner’s Guide to Deep Learning with Ludwig

Joshua Poduska provides a distilled overview of Ludwig including when to use Ludwig’s command-line syntax and when to use its Python API. Introduction New tools are constantly being added to the deep learning ecosystem. It can...

Data Science at The New York Times

Chris Wiggins, Chief Data Scientist at The New York Times, presented "Data Science at the New York Times" at Rev. Wiggins advocated that...

Themes and Conferences per Pacoid, Episode 11

Paco Nathan's latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Introduction Welcome back to our monthly burst of themespotting and...

Product Management for AI

Pete Skomoroch presented “Product Management for AI” at Rev. This post provides a distilled summary, video, and full transcript. Session Summary Pete Skomoroch’s...

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...

Code

Can Data Science Help Us Make Sense of the Mueller Report?

This blog post provides insights on how to apply Natural Language Processing (NLP) techniques. A complementary Domino project is available. The Mueller Report...

Creating Multi-language Pipelines with Apache Spark or Avoid Having to Rewrite spaCy into Java

In this guest post, Holden Karau, Apache Spark Committer, provides insights on how to create multi-language pipelines with Apache Spark and avoid rewriting...

Machine Learning

Make Machine Learning Interpretability More Rigorous

This Domino Data Science Field Note covers a proposed definition of machine learning interpretability, why interpretability matters, and the arguments for considering a...

The Machine Learning Reproducibility Crisis

Pete Warden is the Technical Lead on the TensorFlow Mobile Embedded Team at Google doing Deep Learning. He is formerly the CTO of...

Featured

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...

Featured

Model Management and the Era of the Model-Driven Business

Over the past few years, we’ve seen a new community of data science leaders emerge. Regardless of their industry, we have heard three...

Practical Techniques

MNIST Expanded: 50,000 New Samples Added

This post provides a distilled overview regarding the rediscovery of 50,000 samples within the MNIST dataset.  MNIST: The Potential Danger of Overfitting Recently,...

Manipulating Data with dplyr

Special thanks to Addison-Wesley Professional for permission to excerpt the following "Manipulating data with dplyr" chapter from the book, Programming Skills for Data...

Machine Learning Product Management: Lessons Learned

This Domino Data Science Field Note covers Pete Skomoroch’s recent Strata London talk. It focuses on his ML product management insights and lessons...

Addressing Irreproducibility in the Wild

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer’s "The Ingredients of a Reproducible Machine Learning Model" talk...

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...

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...

Announcing Trial and Domino 3.5: Control Center for Data Science Leaders

Even the most sophisticated data science organizations struggle to keep track of their data science projects. Data science leaders want to know, at...

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...

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