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Make Your Models Matter: What It Takes to Maximize Business Value from Your Machine Learning Initiatives

Cloudera

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. Once a model is deployed, ensuring peak operational performance becomes the challenge. .

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Improve Underwriting Using Data and Analytics

Cloudera

We’ve previously highlighted opportunities to improve digital claims processing with data and AI. To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. Step one: gather the data.

Analytics 100
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Metrics Matter: The 4 Types of Code-Level Data OverOps Collects

OverOps

All the data in the world means nothing if it’s not the right data. But when it comes to delivering reliable software and troubleshooting issues, what is the right data? When it comes to CR, it’s not just about what data you can capture, but how you analyze and leverage it. Transactions & Performance Metrics.

Metrics 207
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Trusted AI Cornerstones: Performance Evaluation

DataRobot

In this installment, I’ll cover four key elements of trusted AI that relate to the performance of a model: data quality, accuracy, robustness and stability, and speed. Trustworthy AI is built on a foundation of high-quality data. When you have the data in hand, assess its quality. Quality Input Means Quality Output.

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Build Trustworthy AI With MLOps

In our eBook, Building Trustworthy AI with MLOps, we look at how machine learning operations (MLOps) helps companies deliver machine learning applications in production at scale. We also look closely at other areas related to trust, including: AI performance, including accuracy, speed, and stability.

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Not Getting the Most From Your Model Ops? Why Businesses Struggle With Data Science and Machine Learning

TIBCO - Connected Intelligence

Companies have begun to recognize the value of integrating data science (DS) and machine learning (ML) across their organization to reap the benefits of the advanced analytics they can provide. What are the barriers keeping businesses from operationalizing data science and machine learning?

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The Future Of The Telco Industry And Impact Of 5G & IoT – Part II

Cloudera

To continue where we left off, as industry players continue to shift toward a more 5G centric network, how is 5G impacting the industry from a data perspective? That requires real-time analytics and companies will have to have the capability to ingest and handle real-time streaming data. . This is the next big opportunity for telcos.

IoT 111