Business Analytics IoT Machine Learning 
AWS Machine Learning - AI
NOVEMBER 1, 2024
He has extensive experience designing end-to-end machine learning and business analytics solutions in finance, operations, marketing, healthcare, supply chain management, and IoT. She innovates and applies machine learning to help AWS customers speed up their AI and cloud adoption.
CIO
OCTOBER 6, 2022
Artificial Intelligence (AI) is fast becoming the cornerstone of business analytics, allowing companies to generate value from the ever-growing datasets generated by today’s business processes. Optimising HPC and AI Workloads.
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Gorilla Logic
MAY 19, 2021
Monetize data with technologies such as artificial intelligence (AI), machine learning (ML), blockchain, advanced data analytics , and more. Create value from the Internet of Things (IoT) and connected enterprise. Some of the most common include cloud, IoT, big data, AI/ML, mobile, and more.
O'Reilly Media - Ideas
JANUARY 4, 2022
Artificial Intelligence and Machine Learning. AWS SageMaker Canvas claims to allow businesspeople to develop Machine Learning applications to solve business problems with no programming experience. Connected Hardware (aka IoT). Please don’t say DAOs. Pete Warden shows how to get started.
AWS Machine Learning - AI
AUGUST 2, 2024
For example, it misses the point that the growth in advertising was primarily driven by using machine learning models to improve relevancy of ads. He has extensive experience designing end-to-end machine learning and business analytics solutions in finance, operations, marketing, healthcare, supply chain management, and IoT.
AWS Machine Learning - AI
JULY 10, 2024
He has extensive experience designing end-to-end machine learning and business analytics solutions in finance, operations, marketing, healthcare, supply chain management, and IoT. Sovik Kumar Nath is an AI/ML and Generative AI Senior Solutions Architect with AWS.
Altexsoft
FEBRUARY 8, 2021
To support the planning process, predictive analytics and machine learning (ML) techniques can be implemented. We have previously described demand forecasting methods and the role of machine learning solutions in a dedicated article. Today, consumers’ preferences are changing momentarily and often chaotically.
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