Data preparation can be complicated. Get an overview of common data preparation tasks like transforming data, splitting datasets and merging multiple data sources. Image: Artem/Adobe Stock Data ...

For design engineers, an artificial intelligence (AI) workflow encompasses four steps: data preparation, modeling, simulation and testing, and deployment. While all steps are important, many engineers ...

We live in a data-rich world where information is ours for the taking. But throwing just any data at your algorithm is a bad idea. With AI, small inconsistencies quickly become big ones. And those ...

Seagate is urging its channel to work with customers to establish the foundations for a successful artificial intelligence roll-out ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...

A new study published in Global Ecology and Biogeography presents a step-by-step guide to compile numerous fossil pollen datasets into a user-specific, standardized and clean compilation—ready for ...

Data integration startup Vectorize AI Inc. says its software is ready to play a critical role in the world of artificial intelligence after closing on a $3.6 million seed funding round today. The ...

Data preparation is an important step in any data analysis. This article offers suggestions for making that process easier and more effective. TechRepublic Get the web's best business technology news, ...