China AI Development Report 2018 (p. 20f.): Using the Web of Science database, this report puts China in the lead ahead of the US and any European country, both for the decade between 2007 and 2017 and in terms of annual output in 2017. Aggregating all European countries out of the top 10 from 2007 to 2017 (the UK, Germany, France, Italy, Spain), they almost catch up to the US and China, reaching 2,096 highly cited papers, compared to 2,241 and 2,349, respectively. The same applies to “hot papers.” Unfortunately, I do not know how they operationalized either “highly cited” or “hot.” Eyeballing combined European output in 2017 alone; China is still in the lead with an increasingly large margin, ahead of the US and Europe, which seem to be roughly tied.
Source: Stefan Torges
Logistic regression is one of the statistical techniques in machine learning used to form prediction models. It is one of the most popular classification algorithms mostly used for binary classification problems (problems with two class values; however, some variants may deal with multiple classes as well). It’s used for various research and industrial problems. Therefore, it is essential to have a good grasp on the logistic regression algorithm. This tutorial is a sneak peek from many of Data Science Dojo’s hands-on exercises from their 5-day 
Recent surveys, studies, forecasts and other quantitative assessments of the progress of AI highlighted the role of augmented intelligence, combining human intelligence with artificial intelligence to produce better results in cybersecurity defense and in getting more business value from the use of IoT data.
