Welcome to the Momenta Learning News on Machine Learning. This is issue 83, please feel free to share this post.
Algorithms have become a ubiquitous and essential part of business operations. Uber uses algorithms to determine customer demand and set pricing accordingly, while Amazon and Netflix use algorithms to nudge their customers to purchase a product or stream a new video they might like. And these examples are just the tip of the iceberg.
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Too many young people get caught in the gap between our flawed educational systems and the “narrow hiring” of corporate employers. On diginomica, I’ve focused more on critiquing talent practices, but that doesn’t mean I’m giving schools a hall pass for the social intimidation, bullying and archaic curricula that too many students lose themselves in.
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Harvard researchers are developing an AI-based cancer-diagnosis system. It may be possible to program computers to interpret pathology images to make cancer diagnoses more accurate. Harvard researchers are developing a machine-learning algorithm, using a “deep learning” approach, which interprets complex patterns observed in real-life data by building multi-layered artificial neural networks.
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After decades of stagnation in research and development of artificial intelligence solutions, machine learning has blossomed again – and its seeds are spreading to financial services. Sofia Lotto Persio reports on how AI is improving the field. In 1997, IBM’s DeepBlue computer programme beat chess master Garry Kasparov in a famous man-versus-machine showdown.
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The data and analytics skills gap is an obstacle to achieving digital transformation, according to a Gartner survey; Microsoft is looking to fill that skills gap with a new online degree program; and Pokemon Go’s creator shares the secrets behind how the game’s maps were created.
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I noticed that Jim Hayden, Savi’s SVP of Data Science, sometimes wears a red cape around the office; but I was curious about his specific role and what it actually means to be a Data Scientist. When I asked, Hayden explained how he uses his technology background, Internet of Things platform, and subject matter expertise Read More…
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Extracting value from a universe of data, analysing sentiment around company names (equities) or about anything else (macro), is a complex journey and we are only about 5% down that road.
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It’s not easy to be healthy. And it’s even harder to be healthy at work, where chances are-despite the vogue for standing desks and the like-you’re parked in a chair for most of the day, focused on a screen. The average workweek, by one recent measure, is now 47 hours and counting.
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Telenor researcher develops data-crunching algorithm to help aid agencies determine literacy rates in developing markets by location
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Sudhir Gupta – So what exactly can we expect from AI in the near term. The class of problems that are best suited for AI solutions are those that involve classification and prediction.
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