Posts tagged machine learning
Highlights From the AI Conference Keynotes

This week, IIA attended The AI Conference presented by O’Reilly Media and Intel AI (#TheAIConf) in New York City. The conference tagline was “Put AI to Work” and it provided an informative and comprehensive overview of the current state of artificial intelligence. Session topics ranged from cutting edge research to new AI tools to production ready use cases.

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84.51° Builds a Machine Learning Machine for Kroger

84.51°’s Chief Operations Officer, Milen Mahadevan, is a champion for automation of processes and products within the organization. 84.51°’s Shop, a custom-built BI platform that allows CPG customers to pull detailed reports about shopping behavior, is a successful example of BI automation.

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Deep Learning: Einstein or Savant?

Once you dig into deep learning, you’ll find that as opposed to being a generally brilliant algorithm akin to Albert Einstein, it is much more akin to a savant like the famous movie character from Rain Man. In other words, a deep learning process is really smart at a specific task or two, but not smart at all for anything else.

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Getting Real About Autonomous Cars

I attended the MIT Disruption Timeline Conference on AI and Machine Learning. There was interesting content on a variety of topics, but a primary focus was on when specific AI capabilities might become generally available. One particular technology addressed was autonomous vehicles. The key question was when 50 percent of vehicles on US roads would be fully autonomous.

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Move Your Analytics Operation from Artisanal to Autonomous

Many organizations today are wondering how to get into machine learning, and what it means for their existing analytics operation. There are many different types of machine learning, and a variety of definitions of the term. I view machine learning as any data-driven approach to explanations, classifications, and predictions that uses automation to construct a model. The computer constructing the model “learns” during the construction process what model best fits the data. Some machine learning models continue to improve their results over time, but most don’t. Machine learning, in other words, is a form of automating your analytics. And it has the potential to make human analysts wildly more productive.

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When Machine Learning Isn't Learning

Terms come in and out of vogue on a regular basis. In recent years, the use of the term Machine Learning has surged. What I struggle with is that many traditional data mining and statistical functions are being folded underneath the machine learning umbrella. Simply classifying algorithms in the machine learning category doesn’t mean that the algorithms have fundamentally changed in any way.

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Will Human Analysts Ever Go Away?

Once a week or so I hear from vendors who are creating the “data scientist in a box.” They say they can use software and hardware to get rid of those pesky human data scientists. Somewhat less frequently I hear from senior managers that they want to pursue analytics without analysts. One online travel website CEO heard me speak, and told me afterward, “I like what you say about analytics. But at my company we are going to do it without analysts—using machine learning instead.”

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