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MLOps and the evolution of data science

IBM Big Data Hub

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. How MLOps will be used within the organization.

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AI Governance: Why our tested framework is essential in an AI world

Collibra

As we speed into a new AI era, there’s a critical element that’s often missing when organizations rush forward in hyper-competitive markets to build scalable, trusted AI programs — and that’s AI governance. An AI governance framework offers a blueprint for how to create successful AI products.

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How to enable trustworthy AI with the right data fabric solution

IBM Big Data Hub

Automated, integrated data science tools help build, deploy, and monitor AI models. With AI governance solutions, a data scientist using standard, open Python libraries and frameworks can have facts about the model building and training automatically collected. Processes that provide AI governance.

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How to choose the best AI platform

IBM Big Data Hub

AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio.

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Office for Students Consultation on Recurrent Funding for 2021-22

CILIP

The consultation includes a Government-mandated policy to increase funding to ?high-value? courses like science, engineering and medicine and to reduce by 50% the funding to ?high courses, including Library and Information Science. Library and Information Science?) high-value? high cost but lower value?

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Introducing watsonx: The future of AI for business

IBM Big Data Hub

It offers its users advanced machine learning, data management , and generative AI capabilities to train, validate, tune and deploy AI systems across the business with speed, trusted data, and governance. It helps facilitate the entire data and AI lifecycle, from data preparation to model development, deployment and monitoring.

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Technology sets the pace of change in content delivery and management

CILIP

ConTech MD Clive Snell says that is why library and information mangers should be looking at the possibilities now. 2019 brings together content delivery and technology, looking at how areas such as AI, machine learning and data science are coming together in the content world. Content delivery pioneers.