CIO Business Intelligence

MARCH 21, 2022

The data that data scientists analyze draws from many sources, including structured, unstructured, or semi-structured data. The more high-quality data available to data scientists, the more parameters they can include in a given model, and the more data they will have on hand for training their models.

Unstructured Data 135

Unstructured Data Data Analytics Analytics Structured Data 135

DataRobot Blog

JANUARY 17, 2023

establishing an appropriate price illiquid securities, predicting where liquidity will be located, and determining appropriate hedge ratios) as well as more generally: the existence of good historical trade data on the assets to be priced (e.g., As discussed, we massively accelerate that process of experimentation.

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). NLG is a software process that transforms structured data into human-language content.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Ontotext

FEBRUARY 14, 2024

As a statistical model, LLM inherently is random. Semantic knowledge graphs combined with LLM allow you to bridge the gap – querying your well-curated and conformed data with natural language. Data quality Knowledge graphs thrive on clean, well-structured data, and they rely on accurate relationships and meaningful connections.

Recreation/Entertainment 105

Recreation/Entertainment Data Integration Modeling Data Quality 105

O'Reilly on Data

APRIL 19, 2021

This makes sense, given that we don’t see heavy usage of tools for model and data versioning. We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. We also asked what kinds of data our “mature” respondents are using. form data).

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

Corinium

APRIL 25, 2019

And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. But I’ll give an example in favour of each.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? How can users drill down, in non-technical ways, to quickly interact with data that explains what correlations seem to matter?

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57