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Machine Learning in Production: Software Architecture

Special thanks to Addison-Wesley Professional for permission to excerpt the following "Software Architecture" chapter from the book, Machine Learning in Production. This chapter excerpt provides data...

Comparing the Functionality of Open Source Natural Language Processing Libraries

In this guest post, Maziyar Panahi and David Talby provide a cheat sheet for choosing open source NLP libraries. What do natural language processing libraries do?...

Highlights from the Maryland Data Science Conference: Deep Learning on Imagery and Text

Niels Kasch, cofounder of Miner & Kasch, an AI and Data Science consulting firm, provides insight from a deep learning session that occurred at the Maryland...

Themes and Conferences per Pacoid, Episode 7

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Introduction Welcome back to our monthly...

On Collaboration Between Data Science, Product, and Engineering Teams

Eugene Mandel, Head of Product at Superconductive Health, recently dropped by Domino HQ to candidly discuss cross-team collaboration within data science. Mandel’s previous leadership roles within...

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...

SHAP and LIME Python Libraries: Part 2 – Using SHAP and LIME

This blog post provides insights on how to use the SHAP and LIME Python libraries in practice and how to interpret their output, helping readers prepare...

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...

Themes and Conferences per Pacoid, Episode 4

Paco Nathan's latest column covers themes that include data privacy, machine ethics, and yes, Don Quixote. Introduction Welcome back to our monthly series about data science....

SHAP and LIME Python Libraries: Part 1 – Great Explainers, with Pros and Cons to Both

This blog post provides a brief technical introduction to the SHAP and LIME Python libraries, followed by code and output to highlight a few pros and...

Making PySpark Work with spaCy: Overcoming Serialization Errors

In this guest post, Holden Karau, Apache Spark Committer, provides insights on how to use spaCy to process text data. Karau is a Developer Advocate at Google, as well...

Themes and Conferences per Pacoid, Episode 3

Paco Nathan‘s column covers themes that include open source, "intelligence is a team sport", and "implications of massive latent hardware". Introduction Welcome to our monthly series...

Justified Algorithmic Forgiveness?

Last week, Paco Nathan referenced Julia Angwin’s recent Strata keynote that covered algorithmic bias. This Domino Data Science Field Note dives a bit deeper into some...

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