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Best of arXiv.org for AI, Machine Learning, and Deep Learning – July 2020 In this recurring monthly feature, we filter recent research papers appearing on the arXiv.org preprint server for compelling subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the past month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – November 2017 In this recurring monthly feature, we filter recent research papers appearing on the arXiv.org preprint server for compelling subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the past mo
Sibyl is an important research project underway at Google that implements machine learning primitives at scale and is widely used within Google. Large scale machine learning is playing an increasingly important role in improving the quality and monetization of Internet properties. A small number of techniques, such as regression, have proven to be widely applicable across Internet properties and a
As I frequently travel in data science circles, I’m hearing more and more about a new kind of tech war: Python vs. R. I’ve lived through many tech wars in the past, e.g. Windows vs. Linux, iPhone vs. Android, etc., but this tech war seems to have a different flavor to it. What feels different in this case is that the application area is the same, namely performing work in data science where the so
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