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This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, di...
Mathematical Engineering of Deep Learning provides a complete and concise overview of deep learning using the language of mathematics. The book provides a self-contained background on machine learning and optimization algorithms and progresses through the key ideas of deep learning. These ideas and architectures include deep neural networks, convolutional models, recurrent models, long/short-term memory, the attention mechanism, transformers, variational auto-encoders, diffusion models, generative adversarial networks, reinforcement learning, and graph neural networks. Concepts are presented using simple mathematical equations together with a concise description of relevant tricks of the tra...
A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
A graduate text on theory and methods using applied probability techniques for scheduling service, manufacturing, and information networks.
This book constitutes the refereed proceedings of the 25th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2019, held in Moscow, Russia, in October 2019. Methods of analytical and stochastic modelling are widely used in engineering to assess and design various complex systems, like computer and communication networks, and manufacturing systems. The 13 full papers presented in this book were carefully reviewed and selected from 22 submissions. The papers detail a diverse range of analysis techniques, including Markov processes, queueing theoretical results, reliability of stochastic systems, stochastic network calculus, and wide variety of applications.
The 16 papers of this proceedings have been selected from the submissions to the 10th International Conference on Queueing Theory and Network Applications (QTNA2015) held on 17-20 August, 2015 in Ha Noi and Ha Long, Vietnam. All contributions discuss theoretical and practical issues connected with queueing theory and its applications in networks and other related fields. The book brings together researchers, scientists and practitioners from the world and offers an open forum to share the latest important research accomplishments and challenging problems in the area of queueing theory and network applications.
This book constitutes the refereed proceedings of the Third Euro-NF International Conference, NET-COOP 2009 held in Eindhoven, The Netherlands, in November 2009. The 18 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on performance analysis methods, wireless, queueing analysis, battery control, distributed control, and cooperation and competition.
Learn to use Julia as a tool for research, and solve problems of genuine interest—like modeling the course of a pandemic—in this practical, hands-on introduction to the language. The Julia programming language is acclaimed in scientific circles for its unparalleled ease, interactivity, and speed. Practical Julia is a comprehensive introduction to the language, making it accessible even if you’re new to programming. Dive in with a thorough guide to Julia’s syntax, data types, and best practices, then transition to craft solutions for challenges in physics, statistics, biology, mathematics, scientific machine learning, and more. Whether you’re solving computational problems, visualiz...
This monograph is a comprehensive and cohesive exposition of power-law statistics. Following a bottom-up construction from a foundational bedrock – the power Poisson process – this monograph presents a unified study of an assortment of power-law statistics including: Pareto laws, Zipf laws, Weibull and Fréchet laws, power Lorenz curves, Lévy laws, power Newcomb-Benford laws, sub-diffusion and super-diffusion, and 1/f and flicker noises. The bedrock power Poisson process, as well as the assortment of power-law statistics, are investigated via diverse perspectives: structural, stochastic, fractal, dynamical, and socioeconomic. This monograph is poised to serve researchers and practitioners – from various fields of science and engineering – that are engaged in analyses of power-law statistics.
Are you looking for creative ways to help your child learn math? You don’t need a special workbook, teacher’s manual, or lesson plans. All you need is an inquiring mind and something interesting to think about. Author Denise Gaskins guides you through activities from preschool to middle school. • Whole numbers, fractions, decimals, and percents. • Patterns, shapes, and geometric design. • Logical thinking, math debates, and strategy games. And Denise makes it easy, with step-by-step instructions so you and your child can explore math together. 70+ Things to Do with a Hundred Chart will launch your family on a voyage of mathematical discovery. Order your copy today. * * * 70+ Things to Do with a Hundred Chart is part of the Playful Math Singles series from Tabletop Academy Press. These short, topical books feature clear explanations and ready-to-play activities.