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Author: Malcolm Mann
Publisher: Macmillan Elt
Published: 2008
Total Pages: 264
ISBN-13: 9780230035416
DOWNLOAD EBOOK →Destination C1 & C2 : Grammar and Vocabulary is the ideal grammar and vocabulary practice book for all advanced students preparing to take any C1 & C2 level exam: e.g. Cambridge CAE and Cambridge CPE.
Author: Malcolm Mann
Publisher:
Published: 2008
Total Pages: 256
ISBN-13: 9783190229550
DOWNLOAD EBOOK →Author: Joseph K. Blitzstein
Publisher: CRC Press
Published: 2014-07-24
Total Pages: 599
ISBN-13: 1466575573
DOWNLOAD EBOOK →Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.
Author: Karl Johan Åström
Publisher: Princeton University Press
Published: 2021-02-02
Total Pages:
ISBN-13: 069121347X
DOWNLOAD EBOOK →The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory
Author: Avrim Blum
Publisher: Cambridge University Press
Published: 2020-01-23
Total Pages: 433
ISBN-13: 1108617360
DOWNLOAD EBOOK →This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author: Steven S. Skiena
Publisher: Springer
Published: 2017-07-01
Total Pages: 445
ISBN-13: 3319554441
DOWNLOAD EBOOK →This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Author: Jure Leskovec
Publisher: Cambridge University Press
Published: 2014-11-13
Total Pages: 480
ISBN-13: 1107077230
DOWNLOAD EBOOK →Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Dan Jurafsky
Publisher: Pearson Education India
Published: 2000-09
Total Pages: 912
ISBN-13: 9788131716724
DOWNLOAD EBOOK →Author: Mark Foley
Publisher: Longman
Published: 2012
Total Pages: 385
ISBN-13: 9781408299159
DOWNLOAD EBOOK →MyGrammarLab is a unique blend of book, online and mobile resources that ensures you have all the information and practice you need to master English grammar.
