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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. more machine learning use casesacross the company. By Bryan Kirschner, Vice President, Strategy at DataStax.

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Data-driven innovation: Machine Learning & Data Analysis

Apiumhub

Machine Learning Algorithms. Machine Learning (ML) algorithms improve automatically through experience and by the use of data, in order to make predictions or decisions without being explicitly programmed to do so. Data Analysis Methods. Data-driven innovation forms a key pillar in this century.

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AI in action: Robotics interoperable operations at the edge

CIO

Storage: Data-intensive AI workloads require techniques for handling large data sets, including compression and deduplication. Keeping data close to where it is generated reduces access times, while distributed storage enables quick access and redundancy.

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Neo4j raises Neo$325M as graph-based data analysis takes hold in enterprise

TechCrunch

Designers will pixel push, frontend engineers will add clicks to make it more difficult to drop out of a soporific Zoom call, but few companies are ever willing to rip out their database storage engine. In the past, most business analysis was built on relational databases. With a graph model, that analysis is a cinch.

Analysis 252
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12 data science certifications that will pay off

CIO

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more. It’s a fundamentals exam, so you don’t need extensive experience to pass.

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Leveraging Microsoft AI: A game changer for manufacturing

CIO

The results are inefficient utilization of edge resources, needlessly complex machine learning models, and impractical use cases, all of which lead to slow or suboptimal adoption by end users. Each edge hosts the ability to compute low- to medium-scale machine learning calculations.

Games 261
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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.