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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. Continuous Operations for Production Machine Learning (COPML) helps companies think about the entire life cycle of an ML model.

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Your Parents Still Don’t Know What a Hashtag Is. Let’s Teach Them the Basics of Machine Learning and Streaming Data

Cloudera

Imagine if you had to explain what machine learning is and how to use it. Cloudera produced a series of ebooks — Production Machine Learning For Dummies , Apache NiFi For Dummies , and Apache Flink For Dummies (coming soon) — to help simplify even the most complex tech topics. Don’t know what data ingestion is?

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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.

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Winning With Data in the Fight Against Fraud, Waste, and Abuse

Cloudera

Namely, agency leaders and staff lack the modernized data infrastructure and tooling needed to fight FWA with such massive amounts of money and data flowing through their agencies. A team approach: rich, scalable data analytics from Cloudera, GAI, Dell, and NVIDIA. FWA is as much a data problem as it is a financial one.

Data 96
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5 Things a Data Scientist Can Do to Stay Current

Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Collecting and accessing data from outside sources.

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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. Code Metrics.

Metrics 207
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Modernizing Data Pipelines using Cloudera Data Platform – Part 1

Cloudera

Data pipelines are in high demand in today’s data-driven organizations. As critical elements in supplying trusted, curated, and usable data for end-to-end analytic and machine learning workflows, the role of data pipelines is becoming indispensable.

Data 89
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10 Keys to AI Success in 2021

In our 10 Keys to AI Success in 2021 eBook, we draw from the engaging conversations we’ve had with guests on our More Intelligent Tomorrow podcast series to show how organizations are overcoming hurdles and realizing the enormous rewards that AI can bring to any organization. How MLOps streamlines machine learning from data to value.

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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.

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Humility in AI: Building Trustworthy and Ethical AI Systems

More and more critical decisions are automated through machine learning models, determining the future of a business or making life-altering decisions for real people. But with the incredible pace of the modern world, AI systems continually face new data patterns, which make it challenging to return reliable predictions.

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Intelligent Process Automation: Boosting Bots with AI and Machine Learning

In Data Robot's new ebook, Intelligent Process Automation: Boosting Bots with AI and Machine Learning, we cover important issues related to IPA, including: What is RPA? Brought to you by Data Robots. What is AI? What is IPA? Steps your organization can take to realize the value of IPA. Common IPA use cases.

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ERP Migration: Why Data Quality Comes First

Automation and machine learning are augmenting human intelligence, tasks, jobs, and changing the systems that organizations need in order not just to compete, but to function effectively and securely in the modern world. Yet the manual processes used to assure data ten, or even five years ago, are no longer fit for purpose.