The Decision Matrix: Bridging AI and Decision Making
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Metrics, decompositions, and decision-making
As I’ve expressed elsewhere, metrics design (and metrics decompositions) are an important part of the data scientist (DS) toolkit. But the leap from one…
Jun 13
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Metrics, decompositions, and decision-making
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October 2024
Machine Learning and Decision-Making: the case for Customer Acquisition Cost Optimization
TL;DR The customer acquisition cost (CAC) is a key metric used by Marketing teams to quantify the effort in acquiring an average customer in a campaign.
Oct 15, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Machine Learning and Decision-Making: the case for Customer Acquisition Cost Optimization
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To Segment or Not: that's the question
"No" is (almost) always the answer
Oct 1, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
To Segment or Not: that's the question
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September 2024
The Analytics of Marathon Running
TL;DR In this post I analyze running data, with the objective of finding optimal training plans for running a marathon.
Sep 17, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
The Analytics of Marathon Running
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June 2024
Levers as features in ML models
Doing optimal decision-making by simulating alternative scenarios with ML
Jun 1, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Levers as features in ML models
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February 2024
Word Embeddings Applications: Part 2
TL;DR Word embeddings lie at the heart of many generative AI (GenAI) applications. In Part 1 of this series, I showed how to construct word embeddings…
Feb 19, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Word Embeddings Applications: Part 2
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Word Embeddings in Large Language Models: Part 1
Methods to construct word embeddings
Feb 13, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Word Embeddings in Large Language Models: Part 1
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Understanding Emergent Capabilities in LLMs
TL;DR In this post, I discuss the problem of “emergent” capabilities in large language models (LLMs).
Feb 2, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Understanding Emergent Capabilities in LLMs
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January 2024
The Importance of Feature Importance to Machine Learning Interpretability
TL;DR In this post, I discuss the importance of features for machine learning interpretability.
Jan 30, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
The Importance of Feature Importance to Machine Learning Interpretability
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Interpretable Machine Learning with Shapley Values
TL;DR Shapley values are commonly used by data scientists to gain insights into the predictive behavior of their machine learning models.
Jan 26, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Interpretable Machine Learning with Shapley Values
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How Will Generative AI Change the Practice of Data Science
TL;DR Generative AI (GenAI) has the potential to disrupt labor markets across the world.
Jan 23, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
How Will Generative AI Change the Practice of Data Science
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Opening the Black Box: The Role of Interpretability in Machine Learning
TL;DR While many machine learning (ML) models boast high predictive performance, they often fall short in offering clear explanations for their…
Jan 19, 2024
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Daniel Vaughan
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The Decision Matrix: Bridging AI and Decision Making
Opening the Black Box: The Role of Interpretability in Machine Learning
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