IBM Big Data Hub

FEBRUARY 6, 2024

Today, these three cloud architecture models are not mutually exclusive; instead, they work in concert to create a hybrid multicloud—an IT infrastructure model that uses a mix of computing environments (e.g., on-premises, private cloud, public cloud, edge) with public cloud services from more than one provider.

Cost-Benefit 101

Cost-Benefit Digital Transformation Software Modeling 101

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Alation

OCTOBER 12, 2022

Academic Quantitative Analysis represents the next chapter in zip code analysis; this form of analysis focuses on the interplay between variables after they have been operationalized, allowing the analyst to study and measure outcomes ( Quantitative and statistical research methods: from hypothesis to results , Bridgmon & Martin, 2006.).

Statistics 52

Statistics Sales Testing Marketing 52

Occam's Razor

MARCH 23, 2021

The other dimension to consider is most Analtyics teams kick into gear after the campaign is concluded, after the customer interaction has taken place in the call center, and after the funds budgeted have already been spent. The first component is a gloriously scaled global creative pre-testing program. Matched market tests.

Analytics 131

Analytics Scorecard Strategy Testing 131

O'Reilly on Data

JULY 25, 2023

I’m a professor who is interested in how we can use LLMs (Large Language Models) to teach programming. Swift Papers felt like a well-scoped project to test how well AI handles a realistic yet manageable real-world programming task. Setting the Stage: Who Am I and What Am I Trying to Build?

Consulting 245

Consulting Interactive Software IT 245

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

Domino Data Lab

APRIL 3, 2019

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84