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Statistics for Data Science Udemy

@machinelearnbot

Do you wish to be a data scientist but don't know where to begin? Want to implement statistics for data science? Want to get acquainted with R programs? Want to learn about the logic involved in computing statistics? If so, then this is the course for you.


Provenance and Pseudo-Provenance for Seeded Learning-Based Automated Test Generation

arXiv.org Machine Learning

Many methods for automated software test generation, including some that explicitly use machine learning (and some that use ML more broadly conceived) derive new tests from existing tests (often referred to as seeds). Often, the seed tests from which new tests are derived are manually constructed, or at least simpler than the tests that are produced as the final outputs of such test generators. We propose annotation of generated tests with a provenance (trail) showing how individual generated tests of interest (especially failing tests) derive from seed tests, and how the population of generated tests relates to the original seed tests. In some cases, post-processing of generated tests can invalidate provenance information, in which case we also propose a method for attempting to construct "pseudo-provenance" describing how the tests could have been (partly) generated from seeds.


Learn Text Mining using R Udemy

@machinelearnbot

As simple as it may sound, text mining involves deriving important, high quality information from text. What do we get from this high quality information? Pretty much anything; text categorization, sentiment analysis, document summarization to name a few.


Artificial Intelligence Research at the University of California, Los Angeles

AI Magazine

Research in AI within the Computer Science Department at the University of California, Los Angeles is loosely composed of three interacting and cooperating groups: (1) the Artificial Intelligence Laboratory, at 3677 Boelter Hall, which is concerned mainly with natural language processing and cognitive modelling, (2) the Cognitive Systems Laboratory, at 4731 Boelter Hall, which studies the nature of search, logic programming, heuristics, and formal methods, and (3) the Robotics and Vision Laboratory, at 3532 Boelter Hall, where research concentrates on robot control in manufacturing, pattern recognition, and expert systems for real-time processing.


Mind Blowing Tech in Learning: AI, VR, and AR featuring Prof. Donald Clark @DonaldClark

#artificialintelligence

Hoy traemos a este espacio esta conferencia titulada "Mind Blowing Tech in Learning: AI, VR, and AR featuring" del Prof. Donald Clark, del Center for Online Innovation in Learning y que nos presentan así: Artificial intelligence (AI) is now the most potent force in IT and will shape learning technology, allowing us to escape from the 30 year paradigm of flat, linear e-learning. During this COIL Fischer Speaker Series presentation, Professor Donald Clark debunks some myths about AI and provide real examples of AI used now in content creation, feedback, assessment and spaced practice. In addition he will talk about virtual reality (VR) & augmented reality (AR) as reviving'learning by doing' and their power to democratize experience. Donald Clark is an EdTech entrepreneur and was CEO and one of the original founders of Epic Group plc, which established itself as the leading company in the UK online learning market, floated on the Stock Market in 1996 and sold in 2005, now CEO of Wildfire Ltd. he also invests in, and advises, EdTech companies. Describing himself as'free from the tyranny of employment', he is a board member of Cogbooks, LearningPool, WildFire and Deputy Chair of Brighton Dome & Arts Festival as well as a Visiting Professor at The University of Derby and Fellow of the Royal Society of Arts (FRSA).