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| caltech masters data science: Feedback Systems Karl Johan Åström, Richard M. Murray, 2021-02-02 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 |
| caltech masters data science: The Mathematics of Data Michael W. Mahoney, John C. Duchi, Anna C. Gilbert, 2018-11-15 Nothing provided |
| caltech masters data science: Strength in Numbers: The Rising of Academic Statistics Departments in the U. S. Alan Agresti, Xiao-Li Meng, 2012-11-02 Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department’s history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional failure story, PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Read here all about how departments such as at Berkeley, Chicago, Harvard, and Stanford started and how they got to where they are today. The book should also be of interests to scholars in the field of disciplinary history. |
| caltech masters data science: Escape from Earth Fraser MacDonald, 2019-06-25 The long-buried truth about the dawn of the Space Age: lies, spies, socialism, and sex magick. Los Angeles, 1930s: Everyone knows that rockets are just toys, the stuff of cranks and pulp magazines. Nevertheless, an earnest engineering student named Frank Malina sets out to prove the doubters wrong. With the help of his friend Jack Parsons, a grandiose and occult-obsessed explosives enthusiast, Malina embarks on a journey that takes him from junk yards and desert lots to the heights of the military-industrial complex. Malina designs the first American rocket to reach space and establishes the Jet Propulsion Laboratory. But trouble soon finds him: the FBI suspects Malina of being a communist. And when some classified documents go missing, will his comrades prove as dependable as his engineering? Drawing on an astonishing array of untapped sources, including FBI documents and private archives, Escape From Earth tells the inspiring true story of Malina's achievements--and the political fear that's kept them hidden. At its heart, this is an Icarus tale: a real life fable about the miracle of human ingenuity and the frailty of dreams. |
| caltech masters data science: Intelligent Systems and Data Science Nguyen Thai-Nghe, |
| caltech masters data science: Machine Learning and Big Data Analytics Rajiv Misra, Rana Omer, Muttukrishnan Rajarajan, Bharadwaj Veeravalli, Nishtha Kesswani, Priyanka Mishra, 2023-06-06 This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers. |
| caltech masters data science: Inference and Learning from Data Ali H. Sayed, 2022-11-30 Discover data-driven learning methods with the third volume of this extraordinary three-volume set. |
| caltech masters data science: High-Dimensional Probability Roman Vershynin, 2018-09-27 An integrated package of powerful probabilistic tools and key applications in modern mathematical data science. |
| caltech masters data science: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-11-11 Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field. |
| caltech masters data science: Data Mining for Scientific and Engineering Applications R.L. Grossman, C. Kamath, P. Kegelmeyer, V. Kumar, R. Namburu, 2013-12-01 Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering. |
| caltech masters data science: Inference and Learning from Data: Volume 2 Ali H. Sayed, 2022-12-22 This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference. |
| caltech masters data science: Decision Neuroscience Jean-Claude Dreher, Léon Tremblay, 2016-09-27 Decision Neuroscience addresses fundamental questions about how the brain makes perceptual, value-based, and more complex decisions in non-social and social contexts. This book presents compelling neuroimaging, electrophysiological, lesional, and neurocomputational models in combination with hormonal and genetic approaches, which have led to a clearer understanding of the neural mechanisms behind how the brain makes decisions. The five parts of the book address distinct but inter-related topics and are designed to serve both as classroom introductions to major subareas in decision neuroscience and as advanced syntheses of all that has been accomplished in the last decade. Part I is devoted to anatomical, neurophysiological, pharmacological, and optogenetics animal studies on reinforcement-guided decision making, such as the representation of instructions, expectations, and outcomes; the updating of action values; and the evaluation process guiding choices between prospective rewards. Part II covers the topic of the neural representations of motivation, perceptual decision making, and value-based decision making in humans, combining neurcomputational models and brain imaging studies. Part III focuses on the rapidly developing field of social decision neuroscience, integrating recent mechanistic understanding of social decisions in both non-human primates and humans. Part IV covers clinical aspects involving disorders of decision making that link together basic research areas including systems, cognitive, and clinical neuroscience; this part examines dysfunctions of decision making in neurological and psychiatric disorders, such as Parkinson's disease, schizophrenia, behavioral addictions, and focal brain lesions. Part V focuses on the roles of various hormones (cortisol, oxytocin, ghrelin/leptine) and genes that underlie inter-individual differences observed with stress, food choices, and social decision-making processes. The volume is essential reading for anyone interested in decision making neuroscience. With contributions that are forward-looking assessments of the current and future issues faced by researchers, Decision Neuroscience is essential reading for anyone interested in decision-making neuroscience. - Provides comprehensive coverage of approaches to studying individual and social decision neuroscience, including primate neurophysiology, brain imaging in healthy humans and in various disorders, and genetic and hormonal influences on decision making - Covers multiple levels of analysis, from molecular mechanisms to neural-systems dynamics and computational models of how we make choices - Discusses clinical implications of process dysfunctions, including schizophrenia, Parkinson's disease, eating disorders, drug addiction, and pathological gambling - Features chapters from top international researchers in the field and full-color presentation throughout with numerous illustrations to highlight key concepts |
| caltech masters data science: Inference and Learning from Data: Volume 1 Ali H. Sayed, 2022-12-22 This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This first volume, Foundations, introduces core topics in inference and learning, such as matrix theory, linear algebra, random variables, convex optimization and stochastic optimization, and prepares students for studying their practical application in later volumes. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 600 end-of-chapter problems (including solutions for instructors), 100 figures, 180 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Inference and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference. |
| caltech masters data science: Getting Up to Speed National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on the Future of Supercomputing, 2005-02-03 Supercomputers play a significant and growing role in a variety of areas important to the nation. They are used to address challenging science and technology problems. In recent years, however, progress in supercomputing in the United States has slowed. The development of the Earth Simulator supercomputer by Japan that the United States could lose its competitive advantage and, more importantly, the national competence needed to achieve national goals. In the wake of this development, the Department of Energy asked the NRC to assess the state of U.S. supercomputing capabilities and relevant R&D. Subsequently, the Senate directed DOE in S. Rpt. 107-220 to ask the NRC to evaluate the Advanced Simulation and Computing program of the National Nuclear Security Administration at DOE in light of the development of the Earth Simulator. This report provides an assessment of the current status of supercomputing in the United States including a review of current demand and technology, infrastructure and institutions, and international activities. The report also presents a number of recommendations to enable the United States to meet current and future needs for capability supercomputers. |
| caltech masters data science: Peterson's Annual Guides to Graduate Study , 1982-12 |
| caltech masters data science: The Cosmos Christopher De Pree, PhD, 2014-10-07 Major new discoveries in space are made almost weekly and there is so much for any new enthusiast to learn and explore. Beginning with the solar system, the Sun, all its planets, major moons, and other features, such as the asteroid belt, Idiot's Guides: The Cosmos is packed with information and features the best photos from various explorations. Beautiful photography and detailed descriptions of the various types of masses are compared to Earth-- making the information as easy to grasp as possible. The book also explores the Milky Way, the various star types, including black holes, galaxy filaments, and much more. Idiot's Guides: The Cosmos is a fascinating and easy-to-understand exploration of the universe. Dozens of stunning, full-color photos highlight the latest discoveries and beauty of space, including the solar system, the Sun, the asteroid belt, the Milky Way, various star types, black holes, and more. |
| caltech masters data science: Astronomical Data Analysis Software and Systems XVI Richard A. Shaw, Frank Hill, 2007 |
| caltech masters data science: Dr. E's Super Stellar Solar System Bethany Ehlmann, Jennifer Swanson, 2018 This stellar book introduces kids to outer space through in-depth info and comic book adventure. Along the way, kids follow explorer Bethany Ehlmann, a member of the NASA Mars Rover Curiosity mission, and her lovable robo-dog, Rover, as they study and protect our amazing solar system. |
| caltech masters data science: Life in the Universe, 5th Edition Jeffrey Bennett, Seth Shostak, Nicholas Schneider, Meredith MacGregor, 2022-08-23 The world’s leading textbook on astrobiology—ideal for an introductory one-semester course and now fully revised and updated Are we alone in the cosmos? How are scientists seeking signs of life beyond our home planet? Could we colonize other planets, moons, or even other star systems? This introductory textbook, written by a team of four renowned science communicators, educators, and researchers, tells the amazing story of how modern science is seeking the answers to these and other fascinating questions. They are the questions that are at the heart of the highly interdisciplinary field of astrobiology, the study of life in the universe. Written in an accessible, conversational style for anyone intrigued by the possibilities of life in the solar system and beyond, Life in the Universe is an ideal place to start learning about the latest discoveries and unsolved mysteries in the field. From the most recent missions to Saturn’s moons and our neighboring planet Mars to revolutionary discoveries of thousands of exoplanets, from the puzzle of life’s beginning on Earth to the latest efforts in the search for intelligent life elsewhere, this book captures the imagination and enriches the reader’s understanding of how astronomers, planetary scientists, biologists, and other scientists make progress at the cutting edge of this dynamic field. Enriched with a wealth of engaging features, this textbook brings any citizen of the cosmos up to speed with the scientific quest to discover whether we are alone or part of a universe full of life. An acclaimed text designed to inspire students of all backgrounds to explore foundational questions about life in the cosmos Completely revised and updated to include the latest developments in the field, including recent exploratory space missions to Mars, frontier exoplanet science, research on the origin of life on Earth, and more Enriched with helpful learning aids, including in-chapter Think about It questions, optional Do the Math and Special Topic boxes, Movie Madness boxes, end-of-chapter exercises and problems, quick quizzes, and much more Supported by instructor’s resources, including an illustration package and test bank, available upon request |
| caltech masters data science: Statistical Regression and Classification Norman Matloff, 2017-09-19 Statistical Regression and Classification: From Linear Models to Machine Learning takes an innovative look at the traditional statistical regression course, presenting a contemporary treatment in line with today's applications and users. The text takes a modern look at regression: * A thorough treatment of classical linear and generalized linear models, supplemented with introductory material on machine learning methods. * Since classification is the focus of many contemporary applications, the book covers this topic in detail, especially the multiclass case. * In view of the voluminous nature of many modern datasets, there is a chapter on Big Data. * Has special Mathematical and Computational Complements sections at ends of chapters, and exercises are partitioned into Data, Math and Complements problems. * Instructors can tailor coverage for specific audiences such as majors in Statistics, Computer Science, or Economics. * More than 75 examples using real data. The book treats classical regression methods in an innovative, contemporary manner. Though some statistical learning methods are introduced, the primary methodology used is linear and generalized linear parametric models, covering both the Description and Prediction goals of regression methods. The author is just as interested in Description applications of regression, such as measuring the gender wage gap in Silicon Valley, as in forecasting tomorrow's demand for bike rentals. An entire chapter is devoted to measuring such effects, including discussion of Simpson's Paradox, multiple inference, and causation issues. Similarly, there is an entire chapter of parametric model fit, making use of both residual analysis and assessment via nonparametric analysis. Norman Matloff is a professor of computer science at the University of California, Davis, and was a founder of the Statistics Department at that institution. His current research focus is on recommender systems, and applications of regression methods to small area estimation and bias reduction in observational studies. He is on the editorial boards of the Journal of Statistical Computation and the R Journal. An award-winning teacher, he is the author of The Art of R Programming and Parallel Computation in Data Science: With Examples in R, C++ and CUDA. |
| caltech masters data science: The Jovian Atmospheres Michael Allison, 1986 |
| caltech masters data science: Astrochemistry: Recent Successes and Current Challenges (IAU S231) International Astronomical Union. Symposium, International Astronomical Union, 2006-04-27 An up-to-date survey of astrochemistry in the early years of the twenty-first century. For researchers and graduate students. |
| caltech masters data science: The Ocean of Truth Henry William Menard, 2014-07-14 Menard begins with the leading hypotheses (such as that the earth expands) and the supporting evidence for each. He traces the crucial work of the 1960s year by year as researchers debated hypotheses in correspondence and at frequent meetings. Throughout the book Professor Menard considers the implications of his story for the sociology of science and the goals of scientific research. Originally published in 1986. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905. |
| caltech masters data science: Handbook of Analytical Studies in Islamic Finance and Economics Zamir Iqbal, Tarik Akin, Nabil El Maghrebi, Abbas Mirakhor, 2020-08-10 This handbook offers a unique and original collection of analytical studies in Islamic economics and finance, and constitutes a humble addition to the literature on new economic thinking and global finance. The growing risks stemming from higher debt, slower growth, and limited room for policy maneuver raise concerns about the ability and propensity of modern economies to find effective solutions to chronic problems. It is important to understand the structural roots of inherent imbalance, persistence-in-error patterns, policy and governance failures, as well as moral and ethical failures. Admittedly, finance and economics have their own failures, with abstract theory bearing little relation with the real economy, uncertainties and vicissitudes of economic life. Economic research has certainly become more empirical despite, or perhaps because of, the lack of guidance from theory. The analytics of Islamic economics and finance may not differ from standard frameworks, methods, and techniques used in conventional economics, but may offer new perspectives on the making of financial crises, nature of credit cycles, roots of financial system instability, and determinants of income disparities. The focus is placed on the logical coherence of Islamic economics and finance, properties of Islamic capital markets, workings of Islamic banking, pricing of Islamic financial instruments, and limits of debt financing, fiscal stimulus and conventional monetary policies, inter alia. Readers with investment, regulatory, and academic interests will find the body of analytical evidence to span many areas of economic inquiry, refuting thereby the false argument that given its religious tenets, Islamic economics is intrinsically narrative, descriptive and not amenable to testable implications. Thus, the handbook may contribute toward a redefinition of a dismal science in search for an elusive balance between rationality, ethics and morality, and toward a remodeling of economies based on risk sharing and prosperity for all humanity |
| caltech masters data science: Peterson's Guide to Graduate Programs in Engineering and Applied Sciences , 1991 |
| caltech masters data science: Big Science, Innovation, and Societal Contributions , 2024-03-26 Big Science, Innovation, and Societal Contributions offers a connection between Big Science and its societal impacts from a multidisciplinary perspective, drawing on physics and astrophysics scholars to explain the reasoning behind their work, and how such knowledge can be applied to everyday life. Through simplifying complex scientific concepts, Big Science, Innovation, and Societal Contributions explains the evolution of Big Science experiments and what it takes to manage and maintain complex scientific experiments with a human centred approach. Further, it examines the motivations behind international efforts to develop capital-intensive and human resource-rich, large-scale multi-national scientific investments to solve fundamental research problems concerning our future. Drawing on reliable scientific evidence, multi-disciplinary perspectives, and personal insights from collider physics, detectors, accelerator, and telescopes research, the volume outlines the mechanisms, benefits, and methodologies, as well as the potential challenges and short-comings, of Big Science, to learn and reflect on for future initiatives. This is an open access title available under the terms of a [CC BY-NC-ND 4.0 International] licence. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. |
| caltech masters data science: The Future of Supercomputing National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on the Future of Supercomputing, 2003-09-08 The Committee on the Future of Supercomputing was tasked to assess prospects for supercomputing technology research and development in support of U.S. needs, to examine key elements of context-the history of supercomputing, the erosion of research investment, the changing nature of problems demanding supercomputing, and the needs of government agencies for supercomputing capabilities-and to assess options for progress. This interim report establishes context-including the history and current state of supercomputing, application requirements, technology evolution, the socioeconomic context-to identify some of the issues that may be explored in more depth in the second phase of the study. |
| caltech masters data science: 108-1 Hearings: Energy And Water Development Appropriations For 2004, Part 6, March 20, 2003, * , 2004 |
| caltech masters data science: Report Series: Committee on Solar and Space Physics National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Space Studies Board, Committee on Solar and Space Physics, 2020-06-26 Report Series: Committee on Solar and Space Physics: Agile Responses to Short-Notice Rideshare Opportunities for the NASA Heliophysics Division explores the kinds of solar and space science that would be enabled by an agile response to rideshare opportunities. This report then explores the types of payloads that are suited to these opportunities and the development and implementation of a new program that would allow agile responses to future short-notice rideshare opportunities. |
| caltech masters data science: NASA Tech Briefs , 2001 |
| caltech masters data science: Encyclopedia of Geomagnetism and Paleomagnetism David Gubbins, Emilio Herrero-Bervera, 2007-07-19 This reference encompasses the fields of Geomagnetism and Paleomagnetism in a single volume. Both sciences have applications in navigation, in the search for minerals and hydrocarbons, in dating rock sequences, and in unraveling past geologic movements such as plate motions they have contributed to a better understanding of the Earth. The book describes in fine detail the current state of knowledge and provides an up-to-date synthesis of the most basic concepts. It is an indispensable working tool not only for geophysicists and geophysics students but also for geologists, physicists, atmospheric and environmental scientists, and engineers. |
| caltech masters data science: Ireland , 1992 |
| caltech masters data science: Astronomical Data Analysis Software and Systems XVIII David A. Bohlender, Daniel Durand, Patrick Dowler, 2009 |
| caltech masters data science: The Evolution of Galaxies and Their Environment David J. Hollenbach, Harley A. Thronson, J. Michael Shull, 1993 |
| caltech masters data science: Discrete Differential Geometry Alexander I. Bobenko TU Berlin, Peter Schröder, John M. Sullivan, Günter M. Ziegler, 2008-03-27 This is the first book on a newly emerging field of discrete differential geometry providing an excellent way to access this exciting area. It provides discrete equivalents of the geometric notions and methods of differential geometry, such as notions of curvature and integrability for polyhedral surfaces. The carefully edited collection of essays gives a lively, multi-facetted introduction to this emerging field. |
| caltech masters data science: Signal Processing and Machine Learning Theory Paulo S.R. Diniz, 2023-07-10 Signal Processing and Machine Learning Theory, authored by world-leading experts, reviews the principles, methods and techniques of essential and advanced signal processing theory. These theories and tools are the driving engines of many current and emerging research topics and technologies, such as machine learning, autonomous vehicles, the internet of things, future wireless communications, medical imaging, etc. - Provides quick tutorial reviews of important and emerging topics of research in signal processing-based tools - Presents core principles in signal processing theory and shows their applications - Discusses some emerging signal processing tools applied in machine learning methods - References content on core principles, technologies, algorithms and applications - Includes references to journal articles and other literature on which to build further, more specific, and detailed knowledge |
| caltech masters data science: Irreducibility and Computational Equivalence Hector Zenil, 2012-12-25 It is clear that computation is playing an increasingly prominent role in the development of mathematics, as well as in the natural and social sciences. The work of Stephen Wolfram over the last several decades has been a salient part in this phenomenon helping founding the field of Complex Systems, with many of his constructs and ideas incorporated in his book A New Kind of Science (ANKS) becoming part of the scientific discourse and general academic knowledge--from the now established Elementary Cellular Automata to the unconventional concept of mining the Computational Universe, from today's widespread Wolfram's Behavioural Classification to his principles of Irreducibility and Computational Equivalence. This volume, with a Foreword by Gregory Chaitin and an Afterword by Cris Calude, covers these and other topics related to or motivated by Wolfram's seminal ideas, reporting on research undertaken in the decade following the publication of Wolfram's NKS book. Featuring 39 authors, its 23 contributions are organized into seven parts: Mechanisms in Programs & Nature Systems Based on Numbers & Simple Programs Social and Biological Systems & Technology Fundamental Physics The Behavior of Systems & the Notion of Computation Irreducibility & Computational Equivalence Reflections and Philosophical Implications. |
| caltech masters data science: GMAT Foundations of Verbal Manhattan Prep, 2020-01-07 Developed for test-takers who need a refresher, Manhattan Prep's GMAT Foundations of Verbal provides a user-friendly review of basic verbal concepts crucial for GMAT success. Written by active instructors with 99th-percentile scores, GMAT Foundations of Verbal is designed to help students, particularly ESL students, who struggle with the basics of the verbal section of the GMAT. The book comes with robust online resources, including a practice test, a question bank and interactive lessons. Designed to be user-friendly for all students, GMAT Foundations of Verbal provides: Review of foundational grammar such as parts of speech and sentence structure Strategies for tackling the three verbal question types—Sentence Correction, Critical Reasoning, and Reading Comprehension Easy-to-follow examples and comprehensive explanations GMAT Foundations of Verbal is an invaluable resource for any student who wants to cement their understanding and build their basic verbal skills for the GMAT. |
| caltech masters data science: "Surely You're Joking, Mr. Feynman!": Adventures of a Curious Character Richard P. Feynman, 2018-02-06 One of the most famous science books of our time, the phenomenal national bestseller that buzzes with energy, anecdote and life. It almost makes you want to become a physicist (Science Digest). Richard P. Feynman, winner of the Nobel Prize in physics, thrived on outrageous adventures. In this lively work that “can shatter the stereotype of the stuffy scientist” (Detroit Free Press), Feynman recounts his experiences trading ideas on atomic physics with Einstein and cracking the uncrackable safes guarding the most deeply held nuclear secrets—and much more of an eyebrow-raising nature. In his stories, Feynman’s life shines through in all its eccentric glory—a combustible mixture of high intelligence, unlimited curiosity, and raging chutzpah. Included for this edition is a new introduction by Bill Gates. |
| caltech masters data science: American University Programs in Computer Science William W. Lau, 1985 |
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5 days ago · Six Caltech students have won summer travel awards to visit countries around the world in fellowships funded by two Caltech alumni.
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Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions and …
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Caltech students work toward undergraduate and graduate degrees alongside their intellectual equals in an academic environment that emphasizes interdisciplinary teamwork, critical …
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Caltech students come from all over the world, bringing diverse experiences, perspectives, and passions. They share an unbridled sense of curiosity and an extraordinary aptitude for …
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Caltech is split into six academic divisions. You'll take classes in each as part of our core curriculum , which emphasizes learning across disciplines. Our job is to make you the best …
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Why Caltech? Why is easy: You can research with Nobel Prize winners, live in L.A., and see what happens when your curiosity is cultivated. But why not is just as important—because before …
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5 days ago · Caltech is small but prizes excellence and ambition. The Institute's extraordinary faculty, students, postdoctoral scholars, and staff are expanding our understanding of the …
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Caltech is a world-renowned research university that develops cutting-edge technologies, addresses fundamental scientific questions, and pursues solutions to the world's greatest …
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