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 Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by... PyTorch Recipes: A Problem-Solution Approach Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look... Digital Dice: Computational Solutions to Practical Probability Problems"Paul Nahin's Digital Dice is a marvelous book, one that is even better than his Duelling Idiots. Nahin presents twenty-one great probability problems, from George Gamow's famous elevator paradox (as corrected by Donald Knuth) to a bewildering puzzle involving two rolls of toilet paper, and he solves them all with the aid...
 Level Sets and Extrema of Random Processes and FieldsLevel Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book... SAS Functions by Example, Second Edition Fully updated for SAS 9.2, Ron Cody's SAS Functions by Example, Second Edition, is a must-have reference for anyone who programs in Base SAS. With the addition of functions new to SAS 9.2, this comprehensive reference manual now includes more than 200 functions, including new character, date and time, distance, probability, sort, and... Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions (Studies in Fuzziness and Soft Computing) Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision...
 Disruption by Design: How to Create Products that Disrupt and then Dominate Markets From Eli Whitney to Henry Ford to Ray Kroc to Steve Jobs, market disruptors have reaped the benefits, including fame and fortune. But do you have to be that rare genius whose unique skills can literally change the world? No. Disrupting a market is a discipline that can be learned. Disruption by Design—a handbook for... Never Bet the Farm: How Entrepreneurs Take Risks, Make Decisionsand How You Can, TooIn Never Bet the Farm two leading entrepreneurs, Anthony Iaquinto and Stephen Spinelli, turn much of the so-called expert advice for entrepreneurs on its head. They show that by preparing for setbacks and using a framework that can help reduce risks and simplify decision making, entrepreneurs can increase their probability for success.... Performance Analysis of Queuing and Computer NetworksPerformance Analysis of Queuing and Computer Networks develops simple models and analytical methods from first principles to evaluate performance metrics of various configurations of computer systems and networks. It presents many concepts and results of probability theory and stochastic processes. After an introduction to...
 Probability and Schrodinger's Mechanics The presentation and interpretation of (non-relativistic) quantum mechanics is a very well-worked area of study; there have to be very good reasons for adding to the literature on this subject. My reasons are (obviously) that I am far from satisfied with much of the published work and find difficulties with some points, in... Probability and Statistics for Computer Scientists Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic... An Inductive Logic Programming Approach to Statistical Relational LearningIn this publication, the author Kristian Kersting has made an assault on one of the hardest integration problems at the heart of Artificial Intelligence research. This involves taking three disparate major areas of research and attempting a fusion among them. The three areas are: Logic Programming, Uncertainty Reasoning and Machine Learning. Every...
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