In this post, I show a network analysis of the R and Python ecosystems in terms of their competitors. To identify the typical substitutes/ competitors of a tool, I use the Google search autofill recommendations. Google search prompts identify the most frequently searched terms which occur after a given string and automatically provides a list of suggestions. Thus, this may be treated as a proxy for the common substitutes people search for against a particular tool. In Fig 1 when I start typing "R vs " in the Google Search bar, Google provides a list of suggestions based on their'autocomplete' feature.

Artificial intelligence and machine learning capabilities are beginning to make an impact within radiology, as vendors start rolling out initiatives to assist professionals in making diagnoses. The radiology profession is ripe for technology--as radiologists deal with an increasing number of images and bear more responsibility in the clinical process. All Health Data Management content is archived after seven days.

Microsoft has released a set of 100,000 questions and answers that artificial intelligence (AI) researchers can use to create systems that can read and answer questions as precisely as a human. "The dataset is called MS MARCO, which stands for Microsoft MAchine Reading COmprehension, and can be used to teach artificial intelligence systems to recognize questions and formulate answers and, eventually, to create systems that can come up with their own answers based on unique questions they have not seen before," said Microsoft in a blog post. By providing realistic questions and answers, the researchers said they can train systems to better deal with the nuances and complexities of questions regular people actually ask, including those queries that have no clear answer or multiple possible answers. "Our dataset is designed not only using real-world data but also removing such constraints so that the new-generation deep learning models can understand the data first before they answer questions," added Li Deng, Partner Research Manager of Microsoft's Deep Learning Technology Centre. The MS MARCO dataset is available for free to any researcher who wants to download it and use it for non-commercial applications, Microsoft said.

IMAGE: This is a map of known and predicted bat hosts of filoviruses, showing hotspots in Southeast Asia. Findings highlight new potential hosts and geographic hotspots worthy of surveillance. So reports a new paper in the journal PLoS Neglected Tropical Diseases. Filoviruses have devastating effects on people and primates, as evidenced by the 2014 Ebola outbreak in West Africa. For nearly 40 years, preventing spillover events has been hampered by an inability to pinpoint which wildlife species harbor and spread the viruses.

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Take a step back for a look at the big picture and it's clear that 2016 was a remarkable year for bots and virtual assistants. Within the span of a few months this spring, Google, Apple, Facebook, and Microsoft all made plans to grow bot ecosystems and invited developers to build bots or virtual assistants integrations for their platforms. If that sounds dry or technical, think of it this way: All of these companies want a relationship with you. They want to be in your home, your smartphone, your car, and your office. They want to be your everything.

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This is the last – for now – installment of my mini-series on sentiment analysis of the Stanford collection of IMDB reviews (originally published on recurrentnull.wordpress.com). So far, we've had a look at classical bag-of-words models and word vectors (word2vec). We saw that from the classifiers used, logistic regression performed best, be it in combination with bag-of-words or word2vec. We also saw that while the word2vec model did in fact model semantic dimensions, it was less successful for classification than bag-of-words, and we explained that by the averaging of word vectors we had to perform to obtain input features on review (not word) level. So the question now is: How would distributed representations perform if we did not have to throw away information by averaging word vectors?

Data Science for IoT vs Classic Data Science: 10 Differences Enterprise AI insights from the AI Europe event in London Is it time to consider data in motion in your big data projects?