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O'Reilly begins to shed some light on the accuracy/complexity tradeoff in machine learning, with An Introduction to Machine Learning Interpretability: An Applied Perspective on Fairness, Accountability, Transparency, and Explainable AI. Get the ebook now!
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Highlights and key takeaways from selected keynote sessions on day 2 of AI Conference San Francisco 2018.
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Highlights and key takeaways include Domain Specific Architectures – the next big thing, Emerging China – evolving from copying ideas to true innovation, and Addressing Risks in AI – Security, Privacy, and Ethics.
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This is an overview of the 4 levels, or "buckets," of data usage in business, starting at monitoring and progressing to automation.
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This post summarizes the contents of a recent O'Reilly article outlining a number of methods for interpreting machine learning models, beyond the usual go-to measures.
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Highlights and key takeaways from day 2 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
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Highlights and key takeaways from day 1 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
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The answer to questions of trust and bias in AI is largely seen in the focus on Explainable AI. Although traditionally viewed as "black boxes", AI and machine learning systems are not ontologically inscrutable.
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- So What is Big Data? - Feb 9, 2017.
We examine what experts say about Big Data – is it like teenage sex? Is it more than just a large and complex collection of data? And how many Vs are there?
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If you're managing big data projects or building distributed data science systems, you will find these online courses very useful: Building Distributed Pipelines for Data, March 1-3 and Managing Successful Big data Projects, March 15-16.
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- Best Data Science Online Courses - Oct 12, 2015.
The number of online data science courses have exploded in recent years and there courses for any needs. Here is a extensive list of free and paid courses from Coursera, DataCamp, Dataquest, edX, Udacity, Udemy, and other major providers.
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Cornelia Levy-Bencheton interviewed 15 women in data to learn how they achieved their current level of success, what motivated them to get there, and their views about opportunities for women.