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Tag: Model Development

Feature Engineering: A Framework and Techniques
This Domino Field Note provides highlights and excerpted slides from Amanda Casari’s “Feature Engineering for Machine Learning” talk at QCon Sao Paulo. Casari is the Principal Product Manager + Data Scientist at Concur Labs. Casari is also the co-author of the book, Feature Engineering for Machine Learning: Principles and Techniques …
Classify all the Things (with Multiple Labels)
Derrick Higgins of American Family Insurance presented a talk, “Classify all the Things (with multiple labels): The most common type of modeling task no one talks about” at Rev. Higgins covers multilabel classification, a few methods used for multiclass prediction, and existing toolkits. This blog post provides highlights, the video, …
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 themes emerge over and over: 1) Companies are recognizing that data science is a competitive differentiator. 2) People are worried their companies are falling behind — that …
Model Evaluation
This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, “Evaluating Machine Learning Models“, including evaluation metrics for supervised learning models and offline evaluation mechanisms. The full in-depth report also includes coverage on offline vs online evaluation mechanisms, hyperparameter tuning and potential A/B testing pitfalls is available …
Data Science Models Build on Each Other
Alex Leeds, presented “Building Up Local Models of Customers” at a Domino Data Science Popup. Leeds discussed how the Squarespace data science team built models to address a key business challenge as well as utilized a complex organizational structure to accelerate data science work. This Domino Data Science Field Note …
On Ingesting Kate Crawford’s “The Trouble with Bias”
Kate Crawford discussed bias at a recent SF-based City Arts and Lectures talk and a recording of the discussion will be broadcast, May 6th, on KQED and local affiliates. Members of Domino were in the live audience for the City Arts talk. This Domino Data Science Field Note provides insights …
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 acquired by Google. He is also an Apple alumnus and blogs at petewarden.com. This post candidly discusses some of the real world reproducibility challenges …