Dataiku

MAY 29, 2020

Delivering on AI and data objectives is not an easy endeavor, and many companies stumble at one of the first (and trickiest) pitfalls: knowing what - and who - to look for when planning for and staffing initiatives.

71

71

O'Reilly on Data

JULY 28, 2020

The Core Responsibilities of the AI Product Manager. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle. If you’re an AI product manager (or about to become one), that’s what you’re signing up for. Identifying the problem. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Its value is so significant that scaling data science has become the new business imperative with organizations spending tens of millions of dollars on data, technology and talent. What is Data Science and How is it Used? What are Data Scientists?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. This post is co-written with Eliad Gat and Oded Lifshiz from Orca Security.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

O'Reilly on Data

JULY 15, 2019

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. What cultural and organizational changes will be needed to accommodate the rise of machine and learning and AI? Image by Ben Lorica.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

Jet Global

MAY 1, 2023

Every application provider has the same goals: to help their users work more efficiently, and to drive user adoption. But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. It will show you what embedded analytics are and how they can help your company.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

DataRobot Blog

JULY 21, 2022

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. With only 87% of projects never making it to production, success hinges on diligent planning. Download Now.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98