DataRobot Blog

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices. For price discovery (e.g.,

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business.

Marketing 362

Marketing Experimentation Metrics Testing 362

Occam's Razor

MARCH 23, 2021

A key part of how this manifested in our work was doing truly super-advanced machine-learning powered analysis to answer hard questions that few can successfully. We’ve chosen to use machine learning algorithms that learn from the underlying structures inside massive amounts of our datasets without explicit programming.

Analytics 131

Analytics Scorecard Strategy Testing 131

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. You saw in the previous chapter that conditioning can break statistical dependence. Introduction.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Insight

MARCH 12, 2020

There was only one problem: literary agents, the gatekeepers of the publishing industry, kept rejecting the book?—?often Using nothing more than a book’s synopsis, the AIgent can surface similar books, genre tags, and sales proxies. Data Collection The AIgent leverages book synopses and book metadata.

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Introduction.

Testing 79

Testing Modeling Machine Learning Metrics 79