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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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Don’t Blink: You’ll Miss Something Amazing!

Cloudera

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way.

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New live online training courses

O'Reilly Media - Ideas

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. AI and machine learning.

Course 67
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Data – the Octane Accelerating Intelligent Connected Vehicles

Cloudera

In addition, moving outside the vehicle, existing fragmented approaches for data management associated with the machine learning lifecycle are limiting the ability to deploy new use cases at scale. The vehicle-to-cloud solution driving advanced use cases.

Data 106
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ChatGPT: le nuove sfide della strategia sui dati nell’era dell’IA generativa

CIO

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

ChatGPT 130
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Re-Thinking the Storage Infrastructure for Business Intelligence

Infinidat

When paired with the accelerated compute so often deployed with AI/ML-driven workloads, traditional storage architectures are severely challenged to keep the processors fed with data and operating efficiently – let alone meeting response time requirements.

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Data Virtualization with Oracle Enterprise Semantic Models

Perficient

This concept plays a key role in a data fabric architecture which aims at isolating the complexity of data management and minimizing disruption for data consumers. Another value-add for the business is that they can access new data sources quicker and in real-time now that the semantic layer requires no data movement or replication.