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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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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 91
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How to Operationalize Your Data Science with Model Ops

TIBCO - Connected Intelligence

Just as you wouldn’t train athletes and not have them compete, the same can be said about data science & machine learning (ML). Model Ops is the process of operationalizing data science by getting data science models into production and then managing them. Model Operations, or Model Ops, is the answer.

Data 72
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10 Steps to Achieve Enterprise Machine Learning Success

Cloudera

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. We recently published a Cloudera Special Edition of Production Machine Learning For Dummies eBook. Chapter six of the eBook focuses on the 10 steps for making ML operational.

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Apiumhub among top IT industry leaders in Code Europe event

Apiumhub

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

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Introducing CDP Data Engineering: Purpose Built Tooling For Accelerating Data Pipelines

Cloudera

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance. Enterprise Data Engineering From the Ground Up.

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How MLOps Enables Machine Learning Production at Scale

DataRobot

This is why businesses are increasingly investing in machine learning operations (MLOps): IDC predicts by 2024, 60% of enterprises will have operationalized their ML workflows by using MLOps. Ebook Building vs. Buying a Machine Learning Management Platform Download Now Working with a vendor will be beneficial.