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The new dawn of Machine Learning

Intercom, Inc.

Building ML products requires balance – it’s pointless to start with the problem if the solution is unattainable, but you shouldn’t start with the tech if it can’t meet real customer needs. ML teams tend to invest a fair share of resources in research that never ships. And you don’t need as much hand engineering of features.

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How much historical data is needed for AI to improve forecast accuracy in workforce management?

DMG Consulting

AI-enabled WFM solutions leverage machine learning (ML), an AI technology that is effective at finding patterns. ML is being used to identify outliers or deviations when validating models and forecasts in an iterative learning process, as well as to automatically identify the algorithm best suited for each set of forecasting criteria.

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Why Qualtrics – Nick Tran – Software Engineer – Seattle, WA

Qualtrics

I graduated from Georgia Tech with a Bachelor’s Degree in Aerospace Engineering. After college, I worked as a structural engineer at an airline and the job was very customer-focused. During my work in Aerospace Engineering, I took some online programming courses. I work as a software engineer for TextIQ R&D team.

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To AI or not to AI? The support leader’s dilemma

Intercom

Embracing a new era The hype around ChatGPT might be very new, but artificial intelligence (AI) and machine learning (ML) have actually been around for quite some time. Up to now, companies would have needed an army of data scientists to make AI and ML work well, but that has all changed. instead, it’s, “When and how will I use it?”

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AI-Enabled WFM Promotes Efficiency and Flexibility

DMG Consulting

Machine learning (ML) helps evaluate algorithms to identify the most effective one to apply to each dataset. Email Address * Submit Deep learning technology is applied to find, analyze, and understand highly complex datasets to improve forecasting and scheduling.

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Ask the Expert: Your Topic Modeling and Machine Learning Questions Answered

Callminer

Is topic modeling supervised machine learning (ML)? We have built a powerful set of tools that can build unsupervised ML topics, but as you know any unsupervised still needs some human intervention, just not in creation. What’s an “engineered category”? The goal is to find the topics in data.

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Bringing creativity to self-service: A CX Moment with Kajabi

Zendesk

Kajabi’s story began when its founder and CEO engineered a complex sprinkler out of PVC pipe. The company has now started to caption those videos to ingest for artificial intelligence (AI) and machine learning (ML). ML, AI is really all about self-service, and the AI component is a search engine. Jared Loman.

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