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| data science in astronomy: Statistics, Data Mining, and Machine Learning in Astronomy Željko Ivezić, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, 2014-01-12 As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers |
| data science in astronomy: Advances in Machine Learning and Data Mining for Astronomy Michael J. Way, Jeffrey D. Scargle, Kamal M. Ali, Ashok N. Srivastava, 2012-03-29 Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines |
| data science in astronomy: Big Data in Astronomy Linghe Kong, Tian Huang, Yongxin Zhu, Shenghua Yu, 2020-06-13 Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world's largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy. - Bridges the gap between radio astronomy and computer science - Includes coverage of the observation lifecycle as well as data collection, processing and analysis - Presents state-of-the-art research and techniques in big data related to radio astronomy - Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST) |
| data science in astronomy: Data Analysis in Astronomy V. di Gesù, L. Scarsi, P. Crane, J.H. Friedman, S. Levialdi, 2012-12-06 The international Workshop on Data Analysis in Astronomy was in tended to give a presentation of experiences that have been acqui red in data analysis and image processing, developments and appli cations that are steadly growing up in Astronomy. The quality and the quantity of ground and satellite observations require more so phisticated data analysis methods and better computational tools. The Workshop has reviewed the present state of the art, explored new methods and discussed a wide range of applications. The topics which have been selected have covered the main fields of interest for data analysis in Astronomy. The Workshop has been focused on the methods used and their significant applications. Results which gave a major contribution to the physical interpre tation of the data have been stressed in the presentations. Atten tion has been devoted to the description of operational system for data analysis in astronomy. The success of the meeting has been the results of the coordinated effort of several people from the organizers to those who presen ted a contribution and/or took part in the discussion. We wish to thank the members of the Workshop scientific committee Prof. M. Ca paccioli, Prof. G. De Biase, Prof. G. Sedmak, Prof. A. Zichichi and of the local organizing committee Dr. R. Buccheri and Dr. M.C. Macca rone together with Miss P. Savalli and Dr. A. Gabriele of the E. Majo rana Center for their support and the unvaluable part in arranging the Workshop. |
| data science in astronomy: Knowledge Discovery in Big Data from Astronomy and Earth Observation Petr Skoda, Fathalrahman Adam, 2020-04-10 Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. - Addresses both astronomy and geosciences in parallel, from a big data perspective - Includes introductory information, key principles, applications and the latest techniques - Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields |
| data science in astronomy: Astronomical Image and Data Analysis J.-L. Starck, F. Murtagh, 2007-06-21 With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with topics that are at or beyond the state of the art. It presents material which is more algorithmically oriented than most alternatives and broaches new areas like ridgelet and curvelet transforms. Throughout the book various additions and updates have been made. |
| data science in astronomy: Statistical Methods for Astronomical Data Analysis Asis Kumar Chattopadhyay, Tanuka Chattopadhyay, 2014-10-01 This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for astronomical problems, including regression techniques, along with their usefulness for data set problems related to size and dimension. Analysis of missing data is an important part of the book because of its significance for work with astronomical data. Both existing and new techniques related to dimension reduction and clustering are illustrated through examples. There is detailed coverage of applications useful for classification, discrimination, data mining and time series analysis. Later chapters explain simulation techniques useful for the development of physical models where it is difficult or impossible to collect data. Finally, coverage of the many R programs for techniques discussed makes this book a fantastic practical reference. Readers may apply what they learn directly to their data sets in addition to the data sets included by the authors. |
| data science in astronomy: Modern Statistical Methods for Astronomy Eric D. Feigelson, G. Jogesh Babu, 2012-07-12 Modern Statistical Methods for Astronomy: With R Applications. |
| data science in astronomy: Scientific Astrophotography Gerald R. Hubbell, 2012-11-09 Scientific Astrophotography is intended for those amateur astronomers who are looking for new challenges, once they have mastered visual observing and the basic imaging of various astronomical objects. It will also be a useful reference for scientifically inclined observers who want to learn the fundamentals of astrophotography with a firm emphasis on the discipline of scientific imaging. This books is not about making beautiful astronomical images; it is about recording astronomical images that are scientifically rigorous and from which accurate data can be extracted. This book is unique in that it gives readers the skills necessary for obtaining excellent images for scientific purposes in a concise and procedurally oriented manner. This not only gets the reader used to a disciplined approach to imaging to maximize quality, but also to maximize the success (and minimize the frustration!) inherent in the pursuit of astrophotography. The knowledge and skills imparted to the reader of this handbook also provide an excellent basis for “beautiful picture” astrophotography! There is a wealth of information in this book – a distillation of ideas and data presented by a diverse set of sources and based on the most recent techniques, equipment, and data available to the amateur astronomer. There are also numerous practical exercises. Scientific Astrophotography is perfect for any amateur astronomer who wants to go beyond just astrophotography and actually contribute to the science of astronomy. |
| data science in astronomy: Essential Radio Astronomy James J. Condon, Scott M. Ransom, 2016-04-05 The ideal text for a one-semester course in radio astronomy Essential Radio Astronomy is the only textbook on the subject specifically designed for a one-semester introductory course for advanced undergraduates or graduate students in astronomy and astrophysics. It starts from first principles in order to fill gaps in students' backgrounds, make teaching easier for professors who are not expert radio astronomers, and provide a useful reference to the essential equations used by practitioners. This unique textbook reflects the fact that students of multiwavelength astronomy typically can afford to spend only one semester studying the observational techniques particular to each wavelength band. Essential Radio Astronomy presents only the most crucial concepts—succinctly and accessibly. It covers the general principles behind radio telescopes, receivers, and digital backends without getting bogged down in engineering details. Emphasizing the physical processes in radio sources, the book's approach is shaped by the view that radio astrophysics owes more to thermodynamics than electromagnetism. Proven in the classroom and generously illustrated throughout, Essential Radio Astronomy is an invaluable resource for students and researchers alike. The only textbook specifically designed for a one-semester course in radio astronomy Starts from first principles Makes teaching easier for astronomy professors who are not expert radio astronomers Emphasizes the physical processes in radio sources Covers the principles behind radio telescopes and receivers Provides the essential equations and fundamental constants used by practitioners Supplementary website includes lecture notes, problem sets, exams, and links to interactive demonstrations An online illustration package is available to professors |
| data science in astronomy: Astronomy and Astrophysics in the New Millennium National Research Council, Division on Engineering and Physical Sciences, Space Studies Board, Board on Physics and Astronomy, Astronomy and Astrophysics Survey Committee, 2002-02-07 In preparing the report, Astronomy and Astrophysics in the New Millenium , the AASC made use of a series of panel reports that address various aspects of ground- and space-based astronomy and astrophysics. These reports provide in-depth technical detail. Astronomy and Astrophysics in the New Millenium: An Overview summarizes the science goals and recommended initiatives in a short, richly illustrated, non-technical booklet. |
| data science in astronomy: New Worlds, New Horizons in Astronomy and Astrophysics National Research Council, Division on Engineering and Physical Sciences, Space Studies Board, Board on Physics and Astronomy, Committee for a Decadal Survey of Astronomy and Astrophysics, 2011-02-04 Driven by discoveries, and enabled by leaps in technology and imagination, our understanding of the universe has changed dramatically during the course of the last few decades. The fields of astronomy and astrophysics are making new connections to physics, chemistry, biology, and computer science. Based on a broad and comprehensive survey of scientific opportunities, infrastructure, and organization in a national and international context, New Worlds, New Horizons in Astronomy and Astrophysics outlines a plan for ground- and space- based astronomy and astrophysics for the decade of the 2010's. Realizing these scientific opportunities is contingent upon maintaining and strengthening the foundations of the research enterprise including technological development, theory, computation and data handling, laboratory experiments, and human resources. New Worlds, New Horizons in Astronomy and Astrophysics proposes enhancing innovative but moderate-cost programs in space and on the ground that will enable the community to respond rapidly and flexibly to new scientific discoveries. The book recommends beginning construction on survey telescopes in space and on the ground to investigate the nature of dark energy, as well as the next generation of large ground-based giant optical telescopes and a new class of space-based gravitational observatory to observe the merging of distant black holes and precisely test theories of gravity. New Worlds, New Horizons in Astronomy and Astrophysics recommends a balanced and executable program that will support research surrounding the most profound questions about the cosmos. The discoveries ahead will facilitate the search for habitable planets, shed light on dark energy and dark matter, and aid our understanding of the history of the universe and how the earliest stars and galaxies formed. The book is a useful resource for agencies supporting the field of astronomy and astrophysics, the Congressional committees with jurisdiction over those agencies, the scientific community, and the public. |
| data science in astronomy: Astronomy 101 Carolyn Collins Petersen, 2013-06-18 Explore the curiosities of our galaxy with this comprehensive, digestible guide to astronomy! Too often, textbooks obscure the beauty and wonder of outer space with tedious discourse that even Galileo would oppose. Astronomy 101 cuts out the boring details and lengthy explanations, and instead, gives you a lesson in astronomy that keeps you engaged as you discover what's hidden beyond our starry sky. From the Big Bang and nebulae to the Milky Way and Sir Isaac Newton, this celestial primer is packed with hundreds of entertaining astronomy facts, charts, and photographs you won't be able to get anywhere else. So whether you’re looking to unravel the mystery behind black holes, or just want to learn more about your favorite planets, Astronomy 101 has all the answers—even the ones you didn’t know you were looking for. |
| data science in astronomy: The Ascent of Information Caleb Scharf, 2022-06-14 “Full of fascinating insights drawn from an impressive range of disciplines, The Ascent of Information casts the familiar and the foreign in a dramatic new light.” —Brian Greene, author of The Elegant Universe Your information has a life of its own, and it’s using you to get what it wants. One of the most peculiar and possibly unique features of humans is the vast amount of information we carry outside our biological selves. But in our rush to build the infrastructure for the 20 quintillion bits we create every day, we’ve failed to ask exactly why we’re expending ever-increasing amounts of energy, resources, and human effort to maintain all this data. Drawing on deep ideas and frontier thinking in evolutionary biology, computer science, information theory, and astrobiology, Caleb Scharf argues that information is, in a very real sense, alive. All the data we create—all of our emails, tweets, selfies, A.I.-generated text and funny cat videos—amounts to an aggregate lifeform. It has goals and needs. It can control our behavior and influence our well-being. And it’s an organism that has evolved right alongside us. This symbiotic relationship with information offers a startling new lens for looking at the world. Data isn’t just something we produce; it’s the reason we exist. This powerful idea has the potential to upend the way we think about our technology, our role as humans, and the fundamental nature of life. The Ascent of Information offers a humbling vision of a universe built of and for information. Scharf explores how our relationship with data will affect our ongoing evolution as a species. Understanding this relationship will be crucial to preventing our data from becoming more of a burden than an asset, and to preserving the possibility of a human future. |
| data science in astronomy: A Companion to Astronomy and Astrophysics Kenneth R. Lang, 2007-01-15 Astronomy and Astrophysics is a comprehensive, fundamental, and up-to-date reference book. It is filled with vital information and basic facts for amateur astronomers and professional astrophysicists, and for anyone interested in the Universe, from the Earth and other planets to the stars, galaxies and beyond. An exceptionally thorough Index cross-references concepts, discoveries and individuals in both the Timeline section and Dictionary section. The combined result is a unique stand-alone reference volume in which the reader can quickly locate information, while also discovering new and unexpected knowledge. |
| data science in astronomy: Handbook of X-ray Astronomy Keith Arnaud, Randall Smith, Aneta Siemiginowska, 2011-09-29 Modern x-ray data, available through online archives, are important for many astronomical topics. However, using these data requires specialized techniques and software. Written for graduate students, professional astronomers and researchers who want to start working in this field, this book is a practical guide to x-ray astronomy. The handbook begins with x-ray optics, basic detector physics and CCDs, before focussing on data analysis. It introduces the reduction and calibration of x-ray data, scientific analysis, archives, statistical issues and the particular problems of highly extended sources. The book describes the main hardware used in x-ray astronomy, emphasizing the implications for data analysis. The concepts behind common x-ray astronomy data analysis software are explained. The appendices present reference material often required during data analysis. |
| data science in astronomy: Observational Astronomy Edmund C. Sutton, 2011-10-13 Astronomy is fundamentally an observational science and as such it is important for astronomers and astrophysicists to understand how their data are collected and analyzed. This book is a comprehensive review of current observational techniques and instruments. Featuring instruments such as Spitzer, Herschel, Fermi, ALMA, Super-Kamiokande, SNO, IceCube, the Auger Observatory, LIGO and LISA, the book discusses the capabilities and limitations of different types of instruments. It explores the sources and types of noise and provides statistical tools necessary for interpreting observational data. Due to the increasingly important role of statistical analysis, the techniques of Bayesian analysis are discussed, along with sampling techniques and model comparison. With topics ranging from fundamental subjects such as optics, photometry and spectroscopy, to neutrinos, cosmic rays and gravitational waves, this book is essential for graduate students in astronomy and physics. Electronic and colour versions of selected figures are available online at www. cambridge.org/9781107010468. |
| data science in astronomy: Grading NASA's Solar System Exploration Program National Research Council, Division on Engineering and Physical Sciences, Space Studies Board, Committee on Assessing the Solar System Exploration Program, 2008-04-25 The NASA Authorization Act of 2005 directed the agency to ask the NRC to assess the performance of each division in the NASA Science directorate at five-year intervals. In this connection, NASA requested the NRC to review the progress the Planetary Exploration Division has made in implementing recommendations from previous, relevant NRC studies. This book provides an assessment of NASA's progress in fulfilling those recommendations including an evaluation how well it is doing and of current trends. The book covers key science questions, flight missions, Mars exploration, research and analysis, and enabling technologies. Recommendations are provided for those areas in particular need of improvement. |
| data science in astronomy: Data Science Applied to Sustainability Analysis Jennifer Dunn, Prasanna Balaprakash, 2021-05-11 Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses |
| data science in astronomy: Electronic Imaging in Astronomy Ian S. McLean, 2008-08-17 The second edition of Electronic Imaging in Astronomy: Detectors and Instrumentation describes the remarkable developments that have taken place in astronomical detectors and instrumentation in recent years – from the invention of the charge-coupled device (CCD) in 1970 to the current era of very large telescopes, such as the Keck 10-meter telescopes in Hawaii with their laser guide-star adaptive optics which rival the image quality of the Hubble Space Telescope. Authored by one of the world’s foremost experts on the design and development of electronic imaging systems for astronomy, this book has been written on several levels to appeal to a broad readership. Mathematical expositions are designed to encourage a wider audience, especially among the growing community of amateur astronomers with small telescopes with CCD cameras. The book can be used at the college level for an introductory course on modern astronomical detectors and instruments, and as a supplement for a practical or laboratory class. |
| data science in astronomy: Intelligent Astrophysics Ivan Zelinka, Massimo Brescia, Dalya Baron, 2021-04-15 This present book discusses the application of the methods to astrophysical data from different perspectives. In this book, the reader will encounter interesting chapters that discuss data processing and pulsars, the complexity and information content of our universe, the use of tessellation in astronomy, characterization and classification of astronomical phenomena, identification of extragalactic objects, classification of pulsars and many other interesting chapters. The authors of these chapters are experts in their field and have been carefully selected to create this book so that the authors present to the community a representative publication that shows a unique fusion of artificial intelligence and astrophysics. |
| data science in astronomy: Source Book in Astronomy, 1900-1950 Harlow Shapley, 1960 The phenomenal growth of modern astronomy, including the invention of the coronagraph and major developments in telescope design and photographic technique, is unparalleled in many centuries. Theories of relativity, the concept and measurement of the expanding universe, the location of sun and planets far from the center of the Milky Way, the exploration of the interiors of stars, the pulsation theory of Cepheid variation, and investigations of interstellar space have profoundly altered the astronomer's approach. These fundamental discoveries are reported in papers by such eminent scientists as Albert Einstein, Sir Arthur S. Eddington, Henry Norris Russell, Sir James Jeans, Meghnad Saha, Otto Struve, Fred L. Whipple, Bernard Lyot, Jan H. Oort, and George Ellery Hale. The Source Book's 69 contributions represent all fields of astronomy. For example, there are reports on the equivalence of mass and energy (E = mc ) of the special theory of relativity; building the 200-inch Palomar telescope; the scattering of galaxies suggesting a rapidly expanding universe; stellar evolution; and the Big Bang and Steady State theories of the universe's origin. |
| data science in astronomy: Numerical Python in Astronomy and Astrophysics Wolfram Schmidt, Marcel Völschow, 2021-07-14 This book provides a solid foundation in the Python programming language, numerical methods, and data analysis, all embedded within the context of astronomy and astrophysics. It not only enables students to learn programming with the aid of examples from these fields but also provides ample motivation for engagement in independent research. The book opens by outlining the importance of computational methods and programming algorithms in contemporary astronomical and astrophysical research, showing why programming in Python is a good choice for beginners. The performance of basic calculations with Python is then explained with reference to, for example, Kepler’s laws of planetary motion and gravitational and tidal forces. Here, essential background knowledge is provided as necessary. Subsequent chapters are designed to teach the reader to define and use important functions in Python and to utilize numerical methods to solve differential equations and landmark dynamical problems in astrophysics. Finally, the analysis of astronomical data is discussed, with various hands-on examples as well as guidance on astronomical image analysis and applications of artificial neural networks. |
| data science in astronomy: Big Data Analytics in Astronomy, Science, and Engineering Shelly Sachdeva, Yutaka Watanobe, Subhash Bhalla, 2023-03-18 This book constitutes the proceedings of the 10th International Conference on Big Data Analytics, BDA 2022, which took place in a hybrid mode during December 2022 in Aizu, Japan. The 14 full papers included in this volume were carefully reviewed and selected from 70 submissions. They were organized in topical sections as follows: big data analytics, networking, social media, search, information extraction, image processing and analysis, spatial, text, mobile and graph data analysis, machine learning, and healthcare. |
| data science in astronomy: Multimessenger Astronomy in Practice Miroslav D. Filipoviâc, Nicholas F. H. Tothill, 2021 The first non-electromagnetic messengers from space were discovered in the early 20th century, but it is only now that multimessenger astronomy is coming into its own. The aim of Multimessenger Astronomy in Practice is to aid an astronomer who is new to research in a particular area of multimessenger astronomy. Covering electromatic radiation from radio through to gamma-rays, and moving on to neutrino, cosmic-ray and gravitational wave astronomy, it gives the reader an overview of the celestial objects detected in each region, the unique methods used to measure them, as well as the principles and methods of data collection, calibration, reduction and analysis. |
| data science in astronomy: Beyond the Atmosphere: Early Years of Space Science Homer Edward Newell, 1980 |
| data science in astronomy: Ultraviolet Astronomy and the Quest for the Origin of Life Ana I. Gomez de Castro, 2021-03-27 Ultraviolet Astronomy and the Quest for the Origin of Life addresses the use of astronomical observations in the ultraviolet range to better understand the generation of complex, life-precursor molecules. The origin of RNA is still under debate but seems to be related to the generation of pools of complex organic molecules submitted to heavy cycles of solution in water and drying. This book investigates whether these cycles require a planetary surface or may occur in space by examining both the theoretical and observational aspects of the role of UV radiation in the origin of life. This book offers the latest advances in these studies for astronomers, astrobiologists and planetary scientists. - Addresses both the theoretical and observational aspects of the role of Ultraviolet (UV) radiation in the origin of life - Builds on the requirements to produce prebiotic molecules in space and the implications for the origin of RNA - Investigates the use of ultraviolet observations related to planetary system formation, the evolution of young planetary disks, and the interaction of stars with planetary atmospheres |
| data science in astronomy: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| data science in astronomy: Machine Learning for Planetary Science Joern Helbert, Mario D'Amore, Michael Aye, Hannah Kerner, 2022-03-22 Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation. - Includes links to a code repository for sharing codes and examples, some of which include executable Jupyter notebook files that can serve as tutorials - Presents methods applicable to everyday problems faced by planetary scientists and sufficient for analyzing large datasets - Serves as a guide for selecting the right method and tools for applying machine learning to particular analysis problems - Utilizes case studies to illustrate how machine learning methods can be employed in practice |
| data science in astronomy: The Glass Universe Dava Sobel, 2016-12-06 From #1 New York Times bestselling author Dava Sobel, the inspiring (People), little-known true story of women's landmark contributions to astronomy A New York Times Book Review Notable Book of 2017 Named one of the best books of the year by NPR, The Economist, Smithsonian, Nature, and NPR's Science Friday Nominated for the PEN/E.O. Wilson Literary Science Writing Award A joy to read.” —The Wall Street Journal In the mid-nineteenth century, the Harvard College Observatory began employing women as calculators, or “human computers,” to interpret the observations their male counterparts made via telescope each night. At the outset this group included the wives, sisters, and daughters of the resident astronomers, but soon the female corps included graduates of the new women's colleges—Vassar, Wellesley, and Smith. As photography transformed the practice of astronomy, the ladies turned from computation to studying the stars captured nightly on glass photographic plates. The “glass universe” of half a million plates that Harvard amassed over the ensuing decades—through the generous support of Mrs. Anna Palmer Draper, the widow of a pioneer in stellar photography—enabled the women to make extraordinary discoveries that attracted worldwide acclaim. They helped discern what stars were made of, divided the stars into meaningful categories for further research, and found a way to measure distances across space by starlight. Their ranks included Williamina Fleming, a Scottish woman originally hired as a maid who went on to identify ten novae and more than three hundred variable stars; Annie Jump Cannon, who designed a stellar classification system that was adopted by astronomers the world over and is still in use; and Dr. Cecilia Helena Payne, who in 1956 became the first ever woman professor of astronomy at Harvard—and Harvard’s first female department chair. Elegantly written and enriched by excerpts from letters, diaries, and memoirs, The Glass Universe is the hidden history of the women whose contributions to the burgeoning field of astronomy forever changed our understanding of the stars and our place in the universe. |
| data science in astronomy: Data Science Vijay Kotu, Bala Deshpande, 2018-11-27 Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: - Gain the necessary knowledge of different data science techniques to extract value from data. - Master the concepts and inner workings of 30 commonly used powerful data science algorithms. - Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more... - Contains fully updated content on data science, including tactics on how to mine business data for information - Presents simple explanations for over twenty powerful data science techniques - Enables the practical use of data science algorithms without the need for programming - Demonstrates processes with practical use cases - Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language - Describes the commonly used setup options for the open source tool RapidMiner |
| data science in astronomy: Space and Astronomy Experiments Pam Walker, Elaine Wood, 2009 Presents new, tested experiments related to the intriguing fields of space science and astronomy. The experiments are designed to promote interest in science both in and out of the classroom, and to improve critical-thinking skills. |
| data science in astronomy: Pathways to Discovery in Astronomy and Astrophysics for the 2020s National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Board on Physics and Astronomy, Space Studies Board, Decadal Survey on Astronomy and Astrophysics 2020 (Astro2020), 2022-08-04 The steering committee was specifically asked to (1) provide an overview of the current state of astronomy and astrophysics science, and technology research in support of that science, with connections to other scientific areas where appropriate; (2) identify the most compelling science challenges and frontiers in astronomy and astrophysics, which shall motivate the committee’s strategy for the future; (3) develop a comprehensive research strategy to advance the frontiers of astronomy and astrophysics for the period 2022-2032 that will include identifying, recommending, and ranking the highest-priority research activities; (4) utilize and recommend decision rules, where appropriate, that can accommodate significant but reasonable deviations in the projected budget or changes in urgency precipitated by new discoveries or unanticipated competitive activities; (5) assess the state of the profession, including workforce and demographic issues in the field, identify areas of concern and importance to the community, and where possible, provide specific, actionable, and practical recommendations to the agencies and community to address these areas. This report proposes a broad, integrated plan for space- and ground-based astronomy and astrophysics for the decade 2023-2032. It also lays the foundations for further advances in the following decade. |
| data science in astronomy: Astronomy and Spiritual Science Elisabeth Vreede, 2007-12 Rudolf Steiner was in fact not merely a phenomenally educated and articulate philosopher but also a Man of Destiny.... By comparison, not only with his contemporaries but with the general history of the Western mind, his stature is almost too excessive to be borne. --Owen Barfield The New Essential Steiner is an illuminating, completely new introduction to the philosophy and essential writings of Rudolf Steiner, introduced and edited by Robert McDermott, who also edited the now-classic Essential Steiner. This new volume offers selections from a wide variety of Steiner's published works, presenting a broad, accessible overview of Anthroposophy. In his introduction, McDermott recounts Steiner's life and work, from his childhood and education to his work as a natural scientist, philosopher, scholar, educator, artist, interpreter of culture, and seer. He places Steiner in relation to major traditions of thought and explores the genesis and development of Anthroposophy. Although Rudolf Steiner is considered by many to be the greatest spiritual seer and philosophical thinker of the twentieth century and is credited with major cultural contributions such as the worldwide Waldorf school movement and the ever-growing biodynamic agricultural movement, he nevertheless remains relatively unknown to both academics and the public. The purpose of this volume is to redress that situation by introducing Steiner's work to a broader audience and making his name more universally recognized. Includes selections from Steiner's writings, which are grouped into chapters that demonstrate the breadth of his thinking and spiritual accomplishments. The New Essential Steiner is an invaluable compendium and introduction to the works that form the foundation of Anthroposophy. |
| data science in astronomy: Big Data Analytics in Astronomy, Science, and Engineering Shelly Sachdeva, |
| data science in astronomy: Adaptive Optics in Astronomy François Roddier, 1999-06-17 Adaptive optics is set to revolutionise the future of astronomy; this is the first book on the subject and is set to become the standard reference. |
| data science in astronomy: Astrostatistics Gutti Jogesh Babu, E.D. Feigelson, 1996-08-01 Modern astronomers encounter a vast range of challenging statistical problems, yet few are familiar with the wealth of techniques developed by statisticians. Conversely, few statisticians deal with the compelling problems confronted in astronomy. Astrostatistics bridges this gap. Authored by a statistician-astronomer team, it provides professionals and advanced students in both fields with exposure to issues of mutual interest. In the first half of the book the authors introduce statisticians to stellar, galactic, and cosmological astronomy and discuss the complex character of astronomical data. For astronomers, they introduce the statistical principles of nonparametrics, multivariate analysis, time series analysis, density estimation, and resampling methods. The second half of the book is organized by statistical topic. Each chapter contains examples of problems encountered astronomical research and highlights methodological issues. The final chapter explores some controversial issues in astronomy that have a strong statistical component. The authors provide an extensive bibliography and references to software for implementing statistical methods. The marriage of astronomy and statistics is a natural one and benefits both disciplines. Astronomers need the tools and methods of statistics to interpret the vast amount of data they generate, and the issues related to astronomical data pose intriguing challenges for statisticians. Astrostatistics paves the way to improved statistical analysis of astronomical data and provides a common ground for future collaboration between the two fields. |
| data science in astronomy: The Astronomy Book Jonathan Henry, 2006-07-31 These five study guides, available for each book in the Wonders of Creation series, are comprehensive and invaluable for teaching settings. With terms, short answer questions, discussion questions and activity ideas, each guide will enhance the learning experience. |
| data science in astronomy: Working Papers National Research Council, Division on Engineering and Physical Sciences, Commission on Physical Sciences, Mathematics, and Applications, Board on Physics and Astronomy, Astronomy and Astrophysics Survey Committee, 1991-02-01 This volume contains working papers on astronomy and astrophysics prepared by 15 non-National Research Council panels in areas ranging from radio astronomy to the status of the profession. |
| data science in astronomy: Big-Data-Analytics in Astronomy, Science, and Engineering Shelly Sachdeva, Yutaka Watanobe, Subhash Bhalla, 2022-02-17 This book constitutes the proceedings of the 9th International Conference on Big Data Analytics, BDA 2021, which took place virtually during December 7–9, 2021. The 15 full papers and 1 short paper included in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections as follows: Data science: systems; data science: architectures; big data analytics in healthcare support systems, information interchange of web data resources; and business analytics. |
Using Data Science in High School Astronomy - arXiv.org
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Report on ISSI forum big data in astronomy rev JW
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Astronomy in the big data era - pdfs.semanticscholar.org
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