Here is the link to coursera course for NLP Pick the software from the The Stanford NLP (Natural Language Processing) Group and input some text to view its parse tree, named entities, part of speech tags, etc.

The bootcamp experience is intense, but we aim to maximize learning while preventing burn-out. Metis believes that a student's brain is like a muscle, and to grow without injury the brain must take time to recover. Therefore, we operate five days a week from 9-6. Each Monday - Thursday consists of three hours of group classroom instruction and five hours of practical skill development and project work. Fridays are "personal investment days" for catch-up, independent work, special guest speakers, career-related work, and/or fun.

Your math teacher lied to you. Sometimes getting your sums wrong is a good thing. So says Joseph Bates, cofounder and CEO of Singular Computing, a company whose computer chips are hardwired to be incapable of performing mathematical calculations correctly. Ask it to add 1 and 1 and you will get answers like 2.01 or 1.98. The Pentagon research agency DARPA funded the creation of Singular's chip because that fuzziness can be an asset when it comes to some of the hardest problems for computers, such as making sense of video or other messy real-world data. "Just because the hardware is sucky doesn't mean the software's result has to be," says Bates.

On November 15th, my credit risk analytics course will be available as e-Learning. Send me an email at Bart.Baesens@gmail.com Bart Baesens holds a master's degree in Business Engineering (option: Management Informatics) and a PhD in Applied Economic Sciences from KU Leuven University (Belgium). He is currently an associate professor at KU Leuven, and a guest lecturer at the University of Southampton (United Kingdom). He has done extensive research on data mining and its applications.

Gradescope, which has graded millions of exam questions, has made the grade itself. The company has raised a 2.6 million round of funding from Freestyle Capital, Bloomberg Beta, Reach Capital and the House Fund. Existing investor K9 Ventures also participated. Dave Samuel from Freestyle will be joining Manu Kumar from K9 Ventures on Gradescope's board. The company, started as a side project at the University of California Berkeley in 2012, makes a software that helps science and engineering professors and teaching assistants grade exam questions on handwritten tests.

A few websites catering to analytics and data science professionals have experienced tremendous growth recently. Organizations such as INFORMS or AMSTAT have seen their traffic explode, targeting high school students to join the ranks of data scientists. Niche publishers providing high quality, actionable content - and run by true data scientists rather than journalists - have also seen spectacular growth. By data science, I mean all disciplines focused on optimizing value through data analysis. It includes operations research, machine learning, data engineering, biostatistics, data mining, business analytics, predictive modeling, data plumbing, statistics and many more.

In this paper, we claim that vector cosine – which is generally considered among the most efficient unsupervised measures for identifying word similarity in Vector Space Models – can be outperformed by an unsupervised measure that calculates the extent of the intersection among the most mutually dependent contexts of the target words. To prove it, we describe and evaluate APSyn, a variant of the Average Precision that, without any optimization, outperforms the vector cosine and the co-occurrence on the standard ESL test set, with an improvement ranging between +9.00% and +17.98%, depending on the number of chosen top contexts.

This paper discusses the Turing Test as an educational activity for undergraduate students. It describes in detail an experiment that we conducted in a first-year non-CS course. We also suggest other pedagogical purposes that the Turing Test could serve.

Recent years have seen increasing interest in AI from outside the AI community. This is partly due to applications based on AI that have been used in real-world domains, for example, the successful deployment of game theory-based decision aids in security domains. This paper describes our teaching approach for introducing the AI concepts underlying security games to diverse audiences. We adapted a game-based research platform that served as a testbed for recent research advances in computational game theory into a set of interactive role-playing games. We guided learners in playing these games as part of our teaching strategy, which also included didactic instruction and interactive exercises on broader AI topics. We describe our experience in applying this teaching approach to diverse audiences, including students of an urban public high school, university undergraduates, and security domain experts who protect wildlife. We evaluate our approach based on results from the games and participant surveys.

Though substantial research has been dedicated towards using technology to improve education, no current methods are as effective as one-on-one tutoring. A critical, though relatively understudied, aspect of effective tutoring is modulating the student's affective state throughout the tutoring session in order to maximize long-term learning gains. We developed an integrated experimental paradigm in which children play a second-language learning game on a tablet, in collaboration with a fully autonomous social robotic learning companion. As part of the system, we measured children's valence and engagement via an automatic facial expression analysis system. These signals were combined into a reward signal that fed into the robot's affective reinforcement learning algorithm. Over several sessions, the robot played the game and personalized its motivational strategies (using verbal and non-verbal actions) to each student. We evaluated this system with 34 children in preschool classrooms for a duration of two months. We saw that (1) children learned new words from the repeated tutoring sessions, (2) the affective policy personalized to students over the duration of the study, and (3) students who interacted with a robot that personalized its affective feedback strategy showed a significant increase in valence, as compared to students who interacted with a non-personalizing robot. This integrated system of tablet-based educational content, affective sensing, affective policy learning, and an autonomous social robot holds great promise for a more comprehensive approach to personalized tutoring.