Ebook: Machine Learning & the Benefits of Working with Federated Data

A detailed look into how data-hungry organizations no longer need to rely on data sharing for collaboration, and can preserve privacy and IP while working across boundaries.
Big or small, organizations the world over are waking up to the value of federated data.

In this ebook, we explore:

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Federated vs centralized
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Examples of federated learning in industry
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Common misconceptions around federated learning
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Unlocking the power of federated learning
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The Apheris approach to federated ML

Recommended Reading

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Understanding the Opportunities: Federated Learning and Consumer Data

In this blog we will explore the ways in which industries, including those reliant on consumer data, can use federated learning as an effective alternative to data sharing.

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How to Choose the Best Federated Learning Platform

How can you evaluate platforms around emerging technologies like federated learning? This article gives you guidance on what your selection criteria should be.

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7 Myths About Federated Learning

In our daily work as a company that builds a platform for federated and privacy-preserving data science, we are often asked to clarify concepts around federated learning with customers. This article highlights 7 common myths about federated learning (FL) and, using practical examples, shows you exactly why they are misleading.