O'Reilly on Data

MARCH 31, 2020

Measurement, tracking, and logging is less of a priority in enterprise software. Consumer product management is typically more bottom-up, driven by large volumes of user feedback and usage tracking data. It turns out that type of data infrastructure is also the foundation needed for building AI products.

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

FEBRUARY 16, 2022

blueberry spacing) is a measure of the model’s interpretability. We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle.

Machine Learning 86

Machine Learning Modeling Metadata Recreation/Entertainment 86

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 166

Analytics Machine Learning Data Science Deep Learning 166

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization is not narrowly “selling data sets ;” it is about improving work and enhancing business performance by better-using data. External monetization opportunities enable different types of data in different formats to be information assets that can be sold or have their value recorded when used.

Strategy 115

Strategy Cost-Benefit Data-driven Measurement 115

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Machine learning model interpretability. measure the subjects’ ability to trust the models’ results.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JUNE 23, 2019

It used deep learning to build an automated question answering system and a knowledge base based on that information. It is like the Google knowledge graph with all those smart, intelligent cards and the ability to create your own cards out of your own data.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning. See Wei et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Occam's Razor

OCTOBER 12, 2017

Ask them what they worry about, ask them what they are solving for, ask them how they measure success, ask them what are two things on the horizon that they are excited about. Optimal Starting SCOTUS Starting Points. If you would like to pursue my personal strategy, here are a collection of cases to use as starting points.

Marketing 136

Marketing Analytics Machine Learning Strategy 136