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How companies around the world apply machine learning

O'Reilly Media - Data

The growing role of data and machine learning cuts across domains and industries. Companies continue to use data to improve decision-making (business intelligence and analytics) and for automation (machine learning and AI). Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

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How to take machine learning from exploration to implementation

O'Reilly Media - Data

Interest in machine learning (ML) has been growing steadily , and many companies and organizations are aware of the potential impact these tools and technologies can have on their underlying operations and processes. Machine Learning in the enterprise". Scalable Machine Learning for Data Cleaning.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly Media - Ideas

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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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Therefore, the majority of machine learning/deep learning frameworks focus on Python APIs.

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5 hot IT budget investments — and 2 going cold

CIO

CIOs anticipate an increased focus on cybersecurity (70%), data analysis (55%), data privacy (55%), AI/machine learning (55%), and customer experience (53%). Besides surgery, the hospital is also investing in robotics for the transportation and delivery of medications.

Budget 363
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From edge to cloud: The critical role of hardware in AI applications

CIO

It is becoming increasingly important in various industries, including healthcare, finance, and transportation. Memory and storage The vast amount of data generated by AI workloads requires high-capacity storage solutions that can handle both structured and unstructured data. Artificial Intelligence, Machine Learning

Hardware 245
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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. It’s also used to deploy machine learning models, data streaming platforms, and databases. That’s not to say it’ll be easy.