Welcome to the Momenta Learning News on Machine Learning. This is issue 27, please feel free to share this post.
Deep learning is a topic that is making big waves at the moment. It is basically a branch of machine learning (another hot topic) that uses algorithms to e.g. recognize objects and understand human speech. Scientists have used deep learning algorithms with multiple processing layers (hence "deep") to make better [...]
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In a few years, email copywriters may spend more time editing and approving copy than writing it, and email designers may not actually design "emails" at all. Why? Because of advancements in machine learning and automation. Litmus (my employer) recently asked more than 1,100 marketers: "Will machine learning, AI, and predictive software ever determine the majority of the content (subject lines, images, copy, etc.)
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Holly Foster Posted March 22, 2016Ten women participating in summer research in the Hamilton College Chemistry, Computer Science and Physics departments have been recognized as Clare Boothe Luce Undergraduate Research Scholars.
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Image recognition is a hot area of research using artificial intelligence, and now IBM offers an online demo to let anyone test out the capabilities offered by its Watson cognitive computing system. Six sample photos are provided for illustration, or you can upload your own and ask Watson to analyze them.
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At the recent RSA Conference it was virtually impossible to find a vendor that was not claiming to use machine learning. Both new and established companies are now touting "machine learning" as a major component of the data science being used in their products. This article answers the following: What the heck is machine learning anyway?
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Amazon Machine Learning gives data science newbies easy-to-use solutions for the most common problems As a physicist, I was originally trained to describe the world in terms of exact equations. Later, as an experimental high-energy particle physicist, I learned to deal with vast amounts of data with errors and with evaluating competing models to describe the data.
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Henri Waelbroeck seems to fit the popular image of the scientist transplanted into the world of high finance and hedge fund trading, the sort of stereotype found in books like "The Fear Index" by Robert Harris. Waelbroeck, director of research at machine learning-enhanced trade execution system Portware, was previously a professor at the Institute of Nuclear Sciences at the National University of Mexico (UNAM).
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Channeling the Cloud CEO Satya Nadella's $1 billion security initiative yields fruit with the Azure Security Center, powered by the technology behind Azure Machine Learning. Microsoft CEO Satya Nadella late last year outlined the company's $1 billion investment in a new, holistic, operations-centric approach to addressing cybersecurity with the formation of its Enterprise Cybersecurity Group (ECG).
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Last week we previewed this in " How Machine Learning APIs are Being Used to Predict Startup Success." Can there be a quantifiable way to hedge investors' risk and ensure they are betting on the right horse? According to the startup "jury" algorithm PreSeries, it's mathematically probable to predict which startup is most likely to succeed and that startup is Novelti.
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How far is too far when it comes to machine learning? We live in the digital age where companies like Google collect information which feeds and informs their algorithms, potentially advancing their technology into the realm of the uncomfortable. When it comes to digital AI and algorithmic predictions, when do we say enough is enough?
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