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Trending Toward Concept Building - A Review of Model Interpretability for Deep Neural Networks

We are at an interesting time in our industry when it comes to validating models - a crossroads of sorts when you think about it. There is an opportunity for practitioners...

Bringing ML to Agriculture: Transforming a Millennia-old Industry

Guest post by Jeff Melching from The Climate Corporation At The Climate Corporation, we aim to help farmers better understand their operations and...

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Domino Paves the Way for the Future of Enterprise Data Science with Latest Release

Today, we annfnaounced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams....

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On Being Model-driven: Metrics and Monitoring

This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability,...

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Time Series with R

This article delves into methods for analyzing multivariate and univariate time series data. A complementary Domino project is available. ...

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Towards Predictive Accuracy: Tuning Hyperparameters and Pipelines

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E....

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Manual Feature Engineering

Many thanks to AWP Pearson for the permission to excerpt "Manual Feature Engineering: Manipulating Data for Fun and Profit" from the book, Machine...

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Themes and Conferences per Pacoid, Episode 9

Paco Nathan's latest article features several emerging threads adjacent to model interpretability. Introduction Welcome back to our monthly burst of...

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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...

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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?

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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...

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Model Evaluation

This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, "Evaluating Machine Learning Models", including evaluation...

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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 Jetpac, which was...

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Domino Honored to Be Named Visionary in Gartner Magic Quadrant

The team at Domino is proud to be named a Visionary for the second year in a row in Gartner’s Magic Quadrant for Data Science and Machine Learning...

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Summertime Analytics: Predicting E. Coli and West Nile Virus

Gene Leynes (Senior Data Scientist) and Nick Lucius (Advanced Analytics) from the City of Chicago discussed two predictive analytics projects that...

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