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SAP Industry Insights Podcast Highlights of 2021 with Host Tom Raftery

Timo Elliott

I recently had the opportunity to sit down with Tom Raftery , host of the SAP Industry Insights Podcast (among others!) Let me ask you another question: what did you enjoy most about hosting these episodes? They are applying machine learning to create more intelligent trade claims management. Timo Elliott: Absolutely.

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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Researchers and practitioners have been using human-labeled data for many years, trying to understand all sorts of abstract concepts that we could not measure otherwise. That’s the focus of this blog post.

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What you need to know about product management for AI

O'Reilly on Data

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.

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Mastering Day 2 Operations with Cloudera

Cloudera

In this blog, we’ll cover the highlights of our recently published Day 2 Operations Guide and why it matters to enterprises. This is the stage where scalability becomes a reality, adapting to growing data and user demands while continuously fortifying security measures. How does Cloudera support Day 2 operations?

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Improved customer satisfaction for global financial information provider

bridgei2i

A global financial information provider – publisher of one of world’s largest business news and financial information in a variety of media. The goal was to measure customer satisfaction level, categorize key topics of customers are talking about and related sentiments. Machine Learning. Business Context.

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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

Probability is the measurement of the likelihood of events. Basics of Machine Learning. Machine learning is the science of building models automatically. Whereas in machine learning, the algorithm understands the data and creates the logic. In supervised learning, a variable is predicted.

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What to Do When AI Fails

O'Reilly on Data

And last is the probabilistic nature of statistics and machine learning (ML). Most AI models decay overtime: This phenomenon, known more widely as model decay , refers to the declining quality of AI system results over time, as patterns in new data drift away from patterns learned in training data.

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