מדריכים מתמטיקה ומדעי המחשב מדעי המחשב

- Artificial intelligence : a modern approach byCall Number: 236 Ru77 2010ISBN: 9780136042594Publication Date: 2010The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications.
- Deep Learning byCall Number: 236.2 Go63ISBN: 9780262035613Publication Date: 2016www.deeplearningbook.org

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. - Probabilistic Graphical Models byCall Number: ONLINE and 236.2 Ko55ISBN: 9780262013192Publication Date: 2009A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions. Most tasks require a person or an automated system to reason--to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms.
- Understanding Machine Learning byCall Number: ONLINE and 236.2 Sh25ISBN: 9781107057135Publication Date: 2014The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
- Digital Image Processing byCall Number: 236.32 Go59 2018ISBN: 9780133356724Publication Date: 2018Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming.
- Computational Vision byCall Number: ONLINEISBN: 9780262133814Publication Date: 2000This text provides an introduction to computational aspects of early vision, in particular, color, stereo, and visual navigation. It integrates approaches from psychophysics and quantitative neurobiology, as well as theories and algorithms from machine vision and photogrammetry. When presenting mathematical material, it uses detailed verbal descriptions and illustrations to clarify complex points. The text is suitable for upper-level students in neuroscience, biology, and psychology who have basic mathematical skills and are interested in studying the mathematical modeling of perception.
- Speech and Language Processing byCall Number: 236.9 Ju73 2009ISBN: 9780131873216Publication Date: 2008-05-16For undergraduate or advanced undergraduate courses in Classical Natural Language Processing, Statistical Natural Language Processing, Speech Recognition, Computational Linguistics, and Human Language Processing. An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology - at all levels and with all modern technologies - this text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. The authors cover areas that traditionally are taught in different courses, to describe a unified vision of speech and language processing. Emphasis is on practical applications and scientific evaluation. An accompanying Website contains teaching materials for instructors, with pointers to language processing resources on the Web. The Second Edition offers a significant amount of new and extended material. Supplements: Click on the "Resources" tab to View Downloadable Files: Solutions Power Point Lecture Slides - Chapters 1-5, 8-10, 12-13 and 24 Now Available! For additional resourcse visit the author website:http://www.cs.colorado.edu/~martin/slp.html

**236** Artificial intelligence, Intelligent agents

See also 258.1 Neural networks

**236.1** Robotics

**236.2** Machine learning, Adaptive systems

See also: 258.2 Cognitive science

**236.3** Pattern recognition, Image processing

**236.31** Digital, signal processing

**236.32** Optical, Vision

**236.33** Audio, Speech

**236.34** Image compression

**236.4** Problem solving, Problem planning

**236.5** Simulation of natural systems, Genetic algorithms

**236.6** Heuristic methods, Expert systems, Fuzzy systems

**236.7** Symbol manipulation

**236.8** Knowledge representation, Automated reasoning, Fuzzy Logic

**236.9** Natural language understanding, Natural language generation