Remove 2019 Remove Machine Learning Remove Modeling
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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for.

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Why you should care about debugging machine learning models

O'Reilly on Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML.

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6 trends framing the state of AI and ML

O'Reilly on Data

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. Unsupervised learning is growing. Growth in ML and AI is unabated.

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Highlights from the Strata Data Conference in London 2019

O'Reilly on Data

Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more. Sustaining machine learning in the enterprise. Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Below you'll find links to highlights from the event.

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Proposals for model vulnerability and security

O'Reilly on Data

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 224
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Highlights from TensorFlow World in Santa Clara, California 2019

O'Reilly on Data

Theodore Summe offers a glimpse into how Twitter employs machine learning throughout its product. Watch “ Personalization of Spotify Home and TensorFlow “ TensorFlow Hub: The platform to share and discover pretrained models for TensorFlow. Watch “ Opening keynote “ Accelerating ML at Twitter.

IoT 194
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The Future of Machine Learning in Cybersecurity

CIO Business Intelligence

Machine learning (ML) is a commonly used term across nearly every sector of IT today. This article will share reasons why ML has risen to such importance in cybersecurity, share some of the challenges of this particular application of the technology and describe the future that machine learning enables.