Core Scientific is among the biggest revival stories for Bitcoin miners whose AI pivot saved its struggling business.

The study identifies two main barriers that obscure AI’s materiality: the narrow focus on data extractivism and the ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the ...

CONTAIN™ represents the next breakthrough in AI-powered ore sorting from TOMRA Mining – a deep learning solution purpose-built to classify complex inclusion-type ores with unprecedented accuracy. By ...

A staged-framework for data preprocessing has been developed to support data mining and help service providers identify customers who might switch to a competitor. The framework pushes the cost ...

Ensuring data quality is the final touch in preprocessing that can make or break your data mining efforts. It involves verifying the accuracy, completeness, and reliability of your dataset after ...

In the realm of data mining, preprocessing is a crucial step that involves transforming raw data into an understandable format. Real-world data is often incomplete, inconsistent, and plagued with ...

Data mining is a technology using which we can extract useful information from data. There are two major issues in data mining first is privacy violation and and second is discrimination.

Here, appropriate data mining algorithms are selected based on the goal of the mining — e.g., classification, regression, clustering, etc. Different algorithms are better suited for different ...

Given the vast data volume, categorizing into internal data (sales, financial, employee, operational, CRM) and external data (market research, government reports, social media) is prudent.