Predictive maintenance involves gathering targeted data for analysis, the results of which will help anticipate potential failures before they occur. Companies opt for this type of maintenance to avoid predictable incidents and repair equipment, assembly lines, or machinery with minimum impact on their operations. “Having to repair a faulty product is disastrous for a manufacturer’s brand image. But shutting down […]
In this presentation, Matthew Zeiler, Ph.D., Founder and CEO of Clarifai Inc, speaks about large convolutional neural networks. These networks have recently demonstrated impressive object recognition performance making real world applications possible.
In this special guest feature, Dr. Ritu Chadha, IEEE Senior member, Executive Director at Vencore Labs, explains one commercial application of machine learning and information theoretics, among other techniques, to big data to reduce human suffering.
Last year, I wrote a review of a useful book that got students up to speed with a key mathematical ingredient of machine learning – linear algebra: The Manga Guide to Linear Algebra. No Starch Press (an excellent source of technical books) just came out with a follow-up title: The Manga Guide to Regression Analysis.
In this special guest feature, Alexander Khaytin, COO for Yandex Data Factory, explains how businesses can introduce “data democracy” and systematic testing and how agility can be introduced into even the most inflexible of organizations, overcoming the barriers prohibiting machine learning adoption and benefit.
Collokia, machine learning company that builds seamless collaboration solutions for software developers, announced the beta launch of its new, collaborative machine-learning platform, designed to foster collaboration within software teams by enabling improved access to information and knowledge.
In this special guest feature, Kerry Liu, CEO and founder of Rubikloud, discusses the importance of machine learning in maximizing the use of customer behavior data in the retail sector.
In the Google TechTalk video presentation below, luminary Jeff Dean discusses the use of Deep Learning at Google – “Large-Scale Deep Learning for Intelligent Computer Systems.”
“Benchmarks, customer experiences, and the technical literature have shown that code modernization can greatly increase application performance on both Intel Xeon and Intel Xeon Phi processors. Colfax Research recently published a study showing that image tagging performance using the open source NeuralTalk2 software can be improved 28x on Intel Xeon processors and by over 55x on the latest Intel Xeon Phi processors.”
In this fourth edition of the O’Reilly Data Science Salary Survey, the input was analyzed from 983 respondents working in the data space, across a variety of industries— representing 45 countries and 45 US states.