Corinium

JUNE 6, 2019

Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers? Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale. Regulations and compliance requirements, especially around pricing, risk selection, etc.,

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 332

Management Machine Learning Experimentation Metrics 332

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. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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. In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Proprietary (often GUI-driven) data science platforms. Code-first data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. The last 10+ years or so have seen Insurance become as data-driven as any vertical industry.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. The term “AI,” meanwhile, is No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20