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Why Machine Learning Solutions are Difficult to Implement without Machine Learning Operations?

The Product Coalition

According to Gartner , 85% of machine learning solutions fail because they use raw data. Data scientists work in isolation from operations specialists, and enterprises spend up to three months deploying an ML model. The peculiarities of MLOps workflow The workflow is based on the development cycle of an ML model.

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Machine Learning (ML) Demystified: What Do You Need to Know About it?

The Product Coalition

The emergence and evolution of data science have been one of the biggest impacts of technology on enterprises. As the web world keeps growing and getting competitive, there’s a dire need for businesses to learn as much as they can about their consumers and the patterns impacting sales and profits. What exactly is Machine Learning (ML)?

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Artificial Intelligence and Machine Learning Help Companies Move Faster

TIBCO - Thought Leadership

Much has been written about the impact of artificial intelligence (AI) and machine learning (ML). Borrowing from the 2007 John McCarthy paper What is Artificial Intelligence? , AI is defined as: “… the science and engineering of making intelligent machines, especially intelligent computer programs.

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Starter KPIs for B2B/Enterprise

Mironov Consulting

I’m often asked what KPIs B2B/enterprise product folks should use, or what OKRs they should choose. Why KPIs from consumer companies don’t fit well with B2B/enterprise. But I find they don’t map well to enterprise companies. Enterprise sales cycles are 6-18 months, with dozens of touches and contributions from every department.

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WatchMojo’s immersion into Deep and Machine Learning

The Product Coalition

In our first attempt, we envisioned gaining a better understanding of our data through machine learning, but truth be told, I grew more confused as the model evolved. Our data scientist was busy getting the dataset ready for a linear regression, but I asked him to work with the lead AI engineer from Erudite AI.

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How AI is Lowering the Barrier to Entry for BI and Analytics

Birst BI

The mainstream arrival of Artificial Intelligence (AI) brings with it the potential to finally meet the demand for actionable, enterprise-wide, fact-based decision making. This takes time and specialized expertise, often involving advanced machine learning algorithms that only skilled data scientists understand.

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Shiplap and Artificial Intelligence: Why AI is Important for Everyone, Not Just Those in Silicon Valley

TIBCO - Thought Leadership

Witness the recent surge in artificial intelligence development: Anyone of a certain age will recall that the kinds of artificial neural networks currently powering Siri and Alexa were also hot way back in the 1980s. The same is true in technology. Our old architecture no longer suits our way of life. Hence, the hype around AI.