O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

IBM Big Data Hub

FEBRUARY 23, 2024

The emergence of NLG has dramatically improved the quality of automated customer service tools, making interactions more pleasant for users, and reducing reliance on human agents for routine inquiries. Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. billion by 2030.

Enterprise 103

Enterprise Interactive Data-driven Key Performance Indicator 103

DataRobot

OCTOBER 20, 2021

Achieving that level of governance at scale requires a common understanding of AI and data concepts. Individuals interacting with AI systems should possess a baseline data literacy, especially in high-risk use cases that require human collaboration at the final decision-making stage.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

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.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

DataRobot Blog

JULY 27, 2022

In this technical post, we’ll focus on some changes we’ve made to allow custom models to operate as an algorithm on Algorithmia, while still feeding predictions, input, and other metrics back to the DataRobot MLOps platform —a true best of both worlds. Data Science Expertise Meets Scalability.

Metrics 52

Metrics Deep Learning Modeling Machine Learning 52

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 84

Marketing Technology Advertising ROI 84

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.

Management 110

Management Machine Learning Experimentation Metrics 110