55 rezultatov
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Statistical Field Theory for Neural Networks(2020) HELIAS, MORITZ,DAHMEN, DAVIDThis book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks.Vezava: Mehka99,52 € -
Will We Ever Have a Quantum Computer?(2020) DYAKONOV, MIKHAIL I.This book addresses a broad community of physicists, engineers, computer scientists and industry professionals, as well as the general public, who are aware of the unprecedented media hype surrounding the supposedly imminent new era of quantum computing.Vezava: Mehka91,86 € -
MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence(2017) KIM PHILVezava: Trda84,21 € -
Core Data Analysis: Summarization, Correlation, and Visualization(2019) MIRKIN, BORISVezava: Mehka84,21 € -
Course in Mathematical Statistics and Large Sample Theory(2016) BHATTACHARYA, RABI,LIN, LIZHEN,PATRANGENARU, VICTORThis graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretiVezava: Trda170,23 € -
Effective DevOps(2016) DAVIS, JENNIFER,DANIELS, RYNSome companies think that adopting devops means bringing in specialists or a host of new tools. With this practical guide, you'll learn why devops is a professional and cultural movement that calls for change from inside your organization.Vezava: Mehka56,06 € -
Graph Theory(2017) DIESTEL, REINHARDFrom the reviews: “This outstanding book cannot be substituted with any other book on the present textbook market. a hell of a good book.” MAA Reviews “A highlight of the book is what is by far the best account in print of the Seymour-Robertson theory oVezava: Trda102,36 € -
Computational Physics(2015) LANDAU, RUBIN H. (OREGON STATE UNIVERSITY, CORVALLIS),PAEZ, MANUEL J. (UNIVERSITY OF ANTIOQUIA, MEDELLIN, COLOMBIA),BORDEIANU, CRISTIAN C. (BUCHAREST UNIVERSITY, ROMANIA)The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working leveVezava: Mehka139,49 € -
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Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning(2020) GALLIER, JEAN H (UNIV OF PENNSYLVANIA, USA),QUAINTANCE, JOCELYN (UNIV OF PENNSYLVANIA, USA)Vezava: Mehka136,80 € -
Basic Elements of Computational Statistics(2017) HARDLE, WOLFGANG KARL,OKHRIN, OSTAP,OKHRIN, YAREMAThis textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R.Vezava: Trda17,50 € -
Introduction to Data Science(2017) IGUAL, LAURA,SEGUI, SANTIThe coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentimeVezava: Mehka61,57 € -
Lectures on Matrix Field Theory(2016) YDRI, BADISThese lecture notes provide a systematic introduction to matrix models of quantum field theories with non-commutative and fuzzy geometries. The book initially focuses on the matrix formulation of non-commutative and fuzzy spaces, followed by a descripVezava: Mehka55,59 €
