Analysis Enterprise Google Cloud Machine Learning 
TechCrunch
JUNE 17, 2021
So it’s exceptional when a new database offering breaks through the barriers and redefines the enterprise. Graph-based data models have become central to modern machine learning and artificial intelligence applications, and are now widely used by data analysts in applications as diverse as marketing to fraud detection.
CIO
APRIL 26, 2024
Count TransUnion among the rising tide of enterprises evolving their identities thanks to IT. “We Under the hood, OneTru’s data management layer, identity layer, analysis layer, and delivery layer leverage a robust data governance framework and standard access control to ensure legal and regulatory compliance and auditability, Achanta says.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
CIO
MAY 8, 2024
Of late, innovative data integration tools are revolutionising how organisations approach data management, unlocking new opportunities for growth, efficiency, and strategic decision-making by leveraging technical advancements in Artificial Intelligence, Machine Learning, and Natural Language Processing. billion by 2025.
Altexsoft
JULY 23, 2020
When speaking of machine learning, we typically discuss data preparation or model building. The fusion of terms “machine learning” and “operations”, MLOps is a set of methods to automate the lifecycle of machine learning algorithms in production — from initial model training to deployment to retraining against new data.
CIO
JANUARY 26, 2024
Mike Amend, Ford’s chief enterprise technology officer, was once CTO for Dell’s global online business. Ford is unique among large automotive manufacturers in its selection of GCP, which Dave McCarthy, research vice president of cloud and edge services at IDC, says provides Ford a strong foundation for data-driven operations.
CIO
AUGUST 11, 2023
How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. It uses sentiment analysis, part-of-speech extraction, and tokenization to parse the intention behind the words.
Confluent
FEBRUARY 6, 2019
Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Therefore, the majority of machine learning/deep learning frameworks focus on Python APIs.
Expert insights. Personalized for you.
252 
Let's personalize your content