The Unofficial Google Data Science Blog

APRIL 23, 2024

If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. One instance of how that exploration led to real business benefits was with the application of machine learning to predict optimal product formulation using a set of desired consumer benefits. Here, they and others share seven ways to create and nurture a culture of innovation.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. Spring 2019 Full Stack Deep Learning Bootcamp (Berkeley).

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

JUNE 27, 2022

It’s not perfect by any means, and we are continuously breaking our own product, but it’s optimized for shipping new features to customers as quickly as we can. You pointed to frontend as a key area in 2019. We knew we had a great product, with a number of paying customers and a fair approach to pricing so churn risk was low.

Software 115

Software Experimentation Testing Marketing 115

Domino Data Lab

JANUARY 24, 2019

Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the market. These data scientists require the flexibility to use a constantly-evolving software and hardware stack to optimize each step of their model lifecycle. Reflections. Jupyter) or IDEs (e.g.,

Data Science 65

Data Science Marketing Data-driven Statistics 65

Jet Global

APRIL 27, 2023

Tax teams of multinational enterprises (MNEs) in the manufacturing industry face increasing challenges to manage business and market risks effectively. For your tax team to be agile, you’ll need to optimize tax technology and processes so you can both spot data insights and mitigate risk.

Manufacturing 52

Manufacturing Marketing Experimentation Risk 52

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150