Domino Data Lab

AUGUST 1, 2021

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

John Wheeler

NOVEMBER 25, 2020

Provide a full view of business operations by delivering forward-looking measures of related risk to help customers successfully navigate the COVID-19 recovery. In addition, 73% of the 760 IRM client interactions in 2019 were business leader focused1. No longer can they rely exclusively on qualitative measures of risk.

Marketing 110

Marketing Risk Management Risk Digital Transformation 110

CIO Business Intelligence

MAY 18, 2023

This step-by-step guide to designing a high-functioning organization helps you understand four team types and interaction patterns and helps you to type and build it. “It By defining team types, their fundamental interactions, and the science behind them, you learn how to better model your organizations according to these definitions. “I

IT 112

IT Software Recreation/Entertainment Technology 112

Smart Data Collective

APRIL 5, 2019

The majority of consumers who have good interaction with a brand on social networks are more likely to recommend that brand to others. For example, the company Tweetdeck was ahead of their game when they recognized the need for businesses to engage with their customers back in 2009. Why is this so important?

Big Data 79

Big Data Interactive Data-driven Metrics 79

Domino Data Lab

JUNE 8, 2021

The intuition here is that a decision boundary that leaves a wider margin between the classes generalises better, which leads us to the key property of support vector machines — they construct a hyperplane in a such a way that the margin of separation between the two classes is maximised (Haykin, 2009). Derivation of a Linear SVM. Fisher, R.

Optimization 76

Optimization Machine Learning Measurement Data Science 76

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? It is hard to account for such tweaking in measurement systems. Some relate to inherent issues with what is being measured.

Metrics 49

Metrics Statistics Data Quality Measurement 49

Occam's Razor

APRIL 8, 2013

First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do. For each of them, write down the KPI you're measuring, and what that KPI should be for you to consider your efforts a success. Measure and decide what to do.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156