Remove 2019 Remove IoT Remove Machine Learning
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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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IoT, Automation and Domopalooza 2019

David Menninger's Analyst Perspectives

Domopalooza 2019 marked the first annual user conference after Domo went public, but the energy, excitement and new feature announcements have not slowed.

IoT 160
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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. Anna Roth discusses human and technical factors and suggests future directions for training machine learning models. Watch “ TensorFlow.js: Bringing machine learning to JavaScript “ MLIR: Accelerating AI.

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.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT).

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New DoE Program Drives Demand For Machine Learning Programmers

Smart Data Collective

Machine learning is leading to numerous changes in the energy industry. The Department of Energy recently announced that it is taking steps to accelerate the integration of machine learning technology in energy research and development. Machine learning is already disrupting the global energy industry on a massive scale.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Collaboration and Sharing.

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