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Formal learning
Results: 810

#	Item
41	TEM Journal–240 Pattern Recognition and Natural Language Processing: State of the Art Mirjana Kocaleva 1,2, Done Stojanov 2, Igor Stojanovik 2, Zoran Zdravev 2 1 Add to Reading List Source URL: www.temjournal.com Language: English - Date: 2016-05-22 13:04:30 Computational linguistics Formal sciences Artificial intelligence Natural language processing Science Linguistics Cybernetics Computational neuroscience Natural language understanding Speech recognition Machine translation Machine learning
42	Microsoft Word - IACIS_2015_Proceedings.doc Add to Reading List Source URL: www.iacis.org Language: English - Date: 2015-09-03 18:21:44 Education Information technology Computing Business intelligence Learning Formal sciences Data management Educational psychology Learning analytics Academic analytics Business analytics Analytics
43	CASE STUDY + How PlayFab solved 3 core data analytics needs and saved 87.5% over DIY with Appuri Add to Reading List Source URL: www.appuri.com Language: English - Date: 2016-08-19 19:13:39 Business intelligence Data analysis Information technology Computing Data management Big data Formal sciences Behavioral analytics Analytics Here Learning analytics
44	Database Meets Deep Learning: Challenges and Opportunities Wei Wang† , Meihui Zhang‡ , Gang Chen§ , H. V. Jagadish# , Beng Chin Ooi† , Kian-Lee Tan† † Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2016-08-03 01:23:00 Computing Concurrent computing Parallel computing Applied mathematics Computational linguistics Computational neuroscience Formal sciences Artificial neural networks Deep learning Machine learning Database Recurrent neural network
45	Wrong side of the tracks: Big Data and Protected Categories Simon DeDeo∗ June 23, 2016 Abstract Add to Reading List Source URL: www.santafe.edu Language: English - Date: 2016-06-27 12:55:13 Science Formal sciences Philosophy Cybernetics Computational neuroscience Algorithm Mathematical logic Theoretical computer science Machine learning Causality Decision tree Artificial intelligence
46	Museums Matter Education Children’s formal education continuously adapts to prepare them for a quickly changing world. In recent years the school curriculum has changed to include Add to Reading List Source URL: www.nationalmuseums.org.uk Language: English - Date: 2015-10-07 09:12:03 Education Educational psychology Museology Educational stages Philosophy of education Museum Curriculum Educational technology Lifelong learning Adult education Teacher Music education
47	Notes on Reading the Washington State Mathematics Standards Transition Documents This document serves as a guide to translate between the 2008 Washington State K-8 Learning Standards for Mathematics and the Common Core S Add to Reading List Source URL: www.k12.wa.us Language: English - Date: 2015-10-22 13:00:23 Mathematics Algebra Elementary arithmetic Binary operations Standards-based education Formal sciences Mathematical notation Common Core State Standards Initiative Fraction Real number Probability Addition
48	International Journal of Artificial Intelligence and Interactive Multimedia, Vol. 2, Nº 2. L.I.M.E. A recommendation model for informal and formal learning, engaged Daniel Burgos UNIR Research, International University Add to Reading List Source URL: www.ijimai.org Language: English - Date: 2016-03-29 07:56:23 Education Educational psychology Learning Instructional design Virtual learning environment Informal learning E-learning Educational technology Collaborative learning Adaptive learning Recommender system Active learning
49	On the Modal Understanding of Triadic Contexts Frithjof Dau and Rudolf Wille Technische Universitat Darmstadt, Fachbereich Mathematik Schlogartenstr. 7, D{64289 Darmstadt, fdau, Add to Reading List Source URL: www.dr-dau.net Language: English - Date: 2007-10-31 23:07:37 Logic Mathematics Philosophy Lattice theory Data mining Formal concept analysis Machine learning Ontology Algebraic logic Boolean algebra Binary relation Modal logic
50	A deep-network solution towards model-less obstacle avoidance Lei Tai1 , Shaohua Li2 , Ming Liu1,2 Abstract— Obstacle avoidance is the core problem for mobile robots. Its objective is to allow mobile robots to explore Add to Reading List Source URL: ram-lab.com Language: English - Date: 2016-08-03 06:46:08 Computational neuroscience Artificial intelligence Cybernetics Neuroscience Artificial neural networks Formal sciences Machine learning Computer vision Convolutional neural network Deep learning Robotics Pattern recognition

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