| cornell data science course: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 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. |
| cornell data science course: Big Data Science in Finance Irene Aldridge, Marco Avellaneda, 2021-01-08 Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners. |
| cornell data science course: Semiparametric Regression with R Jaroslaw Harezlak, David Ruppert, Matt P. Wand, 2018-12-12 This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts. The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R. |
| cornell data science course: Statistical Foundations of Data Science Jianqing Fan, Runze Li, Cun-Hui Zhang, Hui Zou, 2020-09-21 Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning. |
| cornell data science course: Sales Growth McKinsey & Company Inc., Thomas Baumgartner, Homayoun Hatami, Maria Valdivieso de Uster, 2016-04-08 The challenges facing today's sales executives and their organizations continue to grow, but so do the expectations that they will find ways to overcome them and drive consistent sales growth. There are no simple solutions to this situation, but in this thoroughly updated Second Edition of Sales Growth, experts from McKinsey & Company build on their practical blueprint for achieving this goal and explore what world-class sales executives are doing right now to find growth and capture it—as well as how they are creating the capabilities to keep growing in the future. Based on discussions with more than 200 of today's most successful global sales leaders from a wide array of organizations and industries, Sales Growth puts the experiences of these professionals in perspective and offers real-life examples of how they've overcome the challenges encountered in the quest for growth. The book, broken down into five overarching strategies for successful sales growth, shares valuable lessons on everything from how to beat the competition by looking forward, to turning deep insights into simple messages for the front line. Page by page, you'll learn how sales executives are digging deeper than ever to find untapped growth, maximizing emerging markets opportunities, and powering growth through digital sales. You'll also discover what it takes to find big growth in big data, develop the right sales DNA in your organization, and improve channel performance. Three new chapters look at why presales deserve more attention, how to get the most out of marketing, and how technology and outsourcing could entirely reshape the sales function. Twenty new standalone interviews have been added to those from the first edition, so there are now in-depth insights from sales leaders at Adidas, Alcoa, Allianz, American Express, BMW, Cargill, Caterpillar, Cisco, Coca-Cola Enterprises, Deutsche Bank, EMC, Essent, Google, Grainger, Hewlett Packard Enterprise, Intesa Sanpaolo, Itaú Unibanco, Lattice Engines, Mars, Merck, Nissan, P&G, Pioneer Hi-Bred, Salesforce, Samsung, Schneider Electric, Siemens, SWIFT, UPS, VimpelCom, Vodafone, and Würth. Their stories, as well as numerous case studies, touch on some of the most essential elements of sales, from adapting channels to meet changing customer needs to optimizing sales operations and technology, developing sales talent and capabilities, and effectively leading the way to sales growth. Engaging and informative, this timely book details proven approaches to tangible top-line growth and an improved bottom line. Created specifically for sales executives, it will put you in a better position to drive sales growth in today's competitive market. |
| cornell data science course: Handbook of Bird Biology Irby J. Lovette, John W. Fitzpatrick, 2016-06-27 Selected by Forbes.com as one of the 12 best books about birds and birding in 2016 This much-anticipated third edition of the Handbook of Bird Biology is an essential and comprehensive resource for everyone interested in learning more about birds, from casual bird watchers to formal students of ornithology. Wherever you study birds your enjoyment will be enhanced by a better understanding of the incredible diversity of avian lifestyles. Arising from the renowned Cornell Lab of Ornithology and authored by a team of experts from around the world, the Handbook covers all aspects of avian diversity, behaviour, ecology, evolution, physiology, and conservation. Using examples drawn from birds found in every corner of the globe, it explores and distills the many scientific discoveries that have made birds one of our best known - and best loved - parts of the natural world. This edition has been completely revised and is presented with more than 800 full color images. It provides readers with a tool for life-long learning about birds and is suitable for bird watchers and ornithology students, as well as for ecologists, conservationists, and resource managers who work with birds. The Handbook of Bird Biology is the companion volume to the Cornell Lab's renowned distance learning course, www.birds.cornell.edu/courses/home/homestudy/. |
| cornell data science course: SPHR Exam Prep Cathy Winterfield, 2015-12-22 &> Score Higher on the SPHR Exam! We provide you with the proven study tools and expert insight that will help you score higher on your exam Study Tips like the advice and instruction that a personal tutor might provide Notes, Tips, and Cautions provide you with hints and strategies that will help you reduce your mistakes on the exam Comprehensive discussion of all six functional areas covered on the SPHR Exam Practice Questions that include detailed explanations of correct and incorrect answers–so you can learn the material from your success and mistakes COMPREHENSIVE! Succeed with comprehensive learning and practice tests Master the SPHR exam materials in all six tested functional areas Prepare with a comprehensive practice test Analyze your test readiness and areas for further study with topic-focused chapter tests CD-ROM—based practice exam includes an interactive test engine for a meaningful exam experience with 175 questions Learn important test-taking strategies to maximize your score and diminish your anxiety Pearson IT Certification Practice Test The CD-ROM—based practice exam includes an interactive test engine for a realistic exam experience with 175 questions. Includes Exclusive Offer for 70% Off Premium Edition eBook and Practice Test CATHY LEE PANTANO WINTERFIELD, MBA, MSHE, SPHR, ACC, is President of NovaCore Performance Solutions, a firm dedicated to enhancing individual and team workplace performance. She has more than 25 years of experience in HR, training, consulting, management, and coaching for businesses, non-profits, and governmental entities. She previously served as Director of Human Resource Management Programs for Cornell University’s School of Industrial and Labor Relations. Winterfield has presented on many HR and management development topics, and co-authored more than a dozen online courses in these fields. Her books include Performance Appraisals and Mission-Driven Interviewing, as well as the Pearson IT Certification book PHR Exam Prep, Third Edition. |
| cornell data science course: Introduction to Data Science Laura Igual, Santi Seguí, 2017-02-22 This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website. |
| cornell data science course: Foundations of Probabilistic Programming Gilles Barthe, Joost-Pieter Katoen, Alexandra Silva, 2020-12-03 This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core. |
| cornell data science course: Machines as the Measure of Men Michael Adas, 1989 This new edition of what has become a standard account of Western expansion and technological dominance includes a new preface by the author that discusses how subsequent developments in gender and race studies, as well as global technology and politics, enter into conversation with his original arguments. |
| cornell data science course: Statistics and Data Analysis for Financial Engineering David Ruppert, David S. Matteson, 2015-04-21 The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest. |
| cornell data science course: Investing in Financial Research Cheryl Strauss Einhorn, 2019-03-15 Finalist in the Business/Personal Finance category of the 2019 International Book Awards Every day, people around the world make financial decisions. They choose to invest in a stock, sell their holdings in a mutual fund or buy a condominium. These decisions are complex and financially tricky—even for financial professionals. But the literature available on financial research is dated and narrowly focused without any real practical application. Until now there's been a gap in the literature: a book that shows you how to conduct a step by step comprehensive financial investigation that ends in a decision. This book gives you that how. Investing in Financial Research is a guidebook for conducting financial investigations and lays out Cheryl Strauss Einhorn's AREA Method—a research and decision-making system that uniquely controls for bias, focuses on the incentives of others and expands knowledge while improving judgement—and applies it to investigating financial situations. AREA is applicable to all sorts of financial sleuthing, whether for investment analysis or investigative journalism. It allows you to be the expert in your own life. The AREA Method provides you with: *Defined tasks that guide and focus your research on your vision of success; *A structure that isolates your sources, giving you insight into their perspectives, biases and incentives; *Investigative resources, tips and techniques to upgrade your research and analysis beyond document-based sources; *Exercises to foster creativity and originality in your thinking; *A sequence and framework that brings your disparate pieces of research together to build your confidence and conviction about your financial decision. |
| cornell data science course: Social Sequence Analysis Benjamin Cornwell, 2015-08-06 Social sequence analysis includes a diverse and rapidly growing body of methods that social scientists have developed to help study complex ordered social processes, including chains of transitions, trajectories and other ordered phenomena. Social sequence analysis is not limited by content or time scale and can be used in many different fields, including sociology, communication, information science and psychology. Social Sequence Analysis aims to bring together both foundational and recent theoretical and methodological work on social sequences from the last thirty years. A unique reference book for a new generation of social scientists, this book will aid demographers who study life-course trajectories and family histories, sociologists who study career paths or work/family schedules, communication scholars and micro-sociologists who study conversation, interaction structures and small-group dynamics, as well as social epidemiologists. |
| cornell data science course: Slide Rules Traci Nathans-Kelly, Christine G. Nicometo, 2014-03-24 A complete road map to creating successful technical presentations Planning a technical presentation can be tricky. Does the audience know your subject area? Will you need to translate concepts into terms they understand? What sort of visuals should you use? Will this set of bullets truly convey the information? What will your slides communicate to future users? Questions like these and countless others can overwhelm even the most savvy technical professionals. This full-color, highly visual work addresses the unique needs of technical communicators looking to break free of the bulleted slide paradigm. For those seeking to improve their presentations, the authors provide guidance on how to plan, organize, develop, and archive technical presentations. Drawing upon the latest research in cognitive science as well as years of experience teaching seasoned technical professionals, the authors cover a myriad of issues involved in the design of presentations, clearly explaining how to create slide decks that communicate critical technical information. Key features include: Innovative methods for archiving and documenting work through slides in the technical workplace Guidance on how to tailor presentations to diverse audiences, technical and nontechnical alike A plethora of color slides and visual examples illustrating various strategies and best practices Links to additional resources as well as slide examples to inspire on-the-job changes in presentation practices Slide Rules is a first-rate guide for practicing engineers, scientists, and technical specialists as well as anyone wishing to develop useful, engaging, and informative technical presentations in order to become an expert communicator. Find the authors at techartsconsulting.com or on Facebook at: SlideRulesTAC |
| cornell data science course: Materials Science and Engineering for the 1990s National Research Council, Division on Engineering and Physical Sciences, National Materials Advisory Board, Board on Physics and Astronomy, Commission on Engineering and Technical Systems, Commission on Physical Sciences, Mathematics, and Resources, Solid State Sciences Committee, Committee on Materials Science and Engineering, 1989-02-01 Materials science and engineering (MSE) contributes to our everyday lives by making possible technologies ranging from the automobiles we drive to the lasers our physicians use. Materials Science and Engineering for the 1990s charts the impact of MSE on the private and public sectors and identifies the research that must be conducted to help America remain competitive in the world arena. The authors discuss what current and future resources would be needed to conduct this research, as well as the role that industry, the federal government, and universities should play in this endeavor. |
| cornell data science course: Agile Data Science 2.0 Russell Jurney, 2017-06-07 Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track |
| cornell data science course: Grit Angela Duckworth, 2016-05-03 In this instant New York Times bestseller, Angela Duckworth shows anyone striving to succeed that the secret to outstanding achievement is not talent, but a special blend of passion and persistence she calls “grit.” “Inspiration for non-geniuses everywhere” (People). The daughter of a scientist who frequently noted her lack of “genius,” Angela Duckworth is now a celebrated researcher and professor. It was her early eye-opening stints in teaching, business consulting, and neuroscience that led to her hypothesis about what really drives success: not genius, but a unique combination of passion and long-term perseverance. In Grit, she takes us into the field to visit cadets struggling through their first days at West Point, teachers working in some of the toughest schools, and young finalists in the National Spelling Bee. She also mines fascinating insights from history and shows what can be gleaned from modern experiments in peak performance. Finally, she shares what she’s learned from interviewing dozens of high achievers—from JP Morgan CEO Jamie Dimon to New Yorker cartoon editor Bob Mankoff to Seattle Seahawks Coach Pete Carroll. “Duckworth’s ideas about the cultivation of tenacity have clearly changed some lives for the better” (The New York Times Book Review). Among Grit’s most valuable insights: any effort you make ultimately counts twice toward your goal; grit can be learned, regardless of IQ or circumstances; when it comes to child-rearing, neither a warm embrace nor high standards will work by themselves; how to trigger lifelong interest; the magic of the Hard Thing Rule; and so much more. Winningly personal, insightful, and even life-changing, Grit is a book about what goes through your head when you fall down, and how that—not talent or luck—makes all the difference. This is “a fascinating tour of the psychological research on success” (The Wall Street Journal). |
| cornell data science course: Colleges that Change Lives Loren Pope, 1996 The distinctive group of forty colleges profiled here is a well-kept secret in a status industry. They outdo the Ivies and research universities in producing winners. And they work their magic on the B and C students as well as on the A students. Loren Pope, director of the College Placement Bureau, provides essential information on schools that he has chosen for their proven ability to develop potential, values, initiative, and risk-taking in a wide range of students. Inside you'll find evaluations of each school's program and personality to help you decide if it's a community that's right for you; interviews with students that offer an insider's perspective on each college; professors' and deans' viewpoints on their school, their students, and their mission; and information on what happens to the graduates and what they think of their college experience. Loren Pope encourages you to be a hard-nosed consumer when visiting a college, advises how to evaluate a school in terms of your own needs and strengths, and shows how the college experience can enrich the rest of your life. |
| cornell data science course: Problem Solved Cheryl Strauss Einhorn, 2017-04-17 *International Book Awards Finalist It can be messy and overwhelming to figure out how to solve thorny problems. Where do you start? How do you know where to look for information and evaluate its quality and bias? How can you feel confident that you are making a careful and thoroughly researched decision? Whether you are deciding between colleges, navigating a career decision, helping your aging parents find the right housing, or expanding your business, Problem Solved will show you how to use the powerful AREA Method to make complex personal and professional decisions with confidence and conviction. Cheryl’s AREA Method coaches you to make smarter, better decisions because it: Recognizes that research is a fundamental part of decision making and breaks down the process into a series of easy-to-follow steps. Solves for problematic mental shortcuts such as bias, judgment, and assumptions. Builds in strategic stops that help you chunk your learning, stay focused, and make your work work for you. Provides a flexible and repeatable process that acts as a feedback loop. Life is filled with uncertainty, but that uncertainty needn’t hobble us. Problem Solved offers a proactive way to work with, and work through, ambiguity to make thoughtful, confident decisions despite our uncertain and volatile world. |
| cornell data science course: Statistics for Finance Erik Lindström, Henrik Madsen, Jan Nygaard Nielsen, 2016-04-21 Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Itō’s formula, the Black–Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives, identify interest rate models, value bonds, estimate parameters, and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues. In addition, end-of-chapter exercises develop students’ financial reasoning skills. |
| cornell data science course: Applied Magnetism R. Gerber, C.D. Wright, G. Asti, 2013-03-09 This book is based on the contributions to a course, entitled Applied Magnetism, which was the 25th Course of the International School of Materials Science and Technology. The Course was held as a NATO Advanced Study Institute at the Ettore Majorana Centre in Erice, Sicily, Italy between the 1st and 12th July 1992, and attracted almost 70 participants from 15 different countries. The book deals with the theory, experiments and applications of the main topical areas of applied magnetism. These selected areas include the physics of magnetic recording, magnetic and magneto-optic recording devices, systems and media, magnetic fine particles, magnetic separation, domains and domain walls in soft magnetic materials, permanent magnets, magnetoresistance, thin film magneto-optics, and finally, microwave, optical and computational magnetics. The material is organised into I 0 self-contained chapters which together provide a comprehensive coverage of the subject of applied magnetism. The aim is to emphasise the connection between the fundamental theoretical concepts, key experiments and the important technological developments which have been achieved in this field up to the present time. Moreover, when and where possible, pointers to future trends are indicated which hopefully, together with the background material, will promote further advancement of research. The organizing committee would like to acknowledge the sponsorship of the NATO Scientific Affairs Division, the National Science Foundation of the USA, the Science and Engineering Research Council of the UK, the Italian Ministry of Education, the Italian Ministry of University and Scientific Research and the Sicilian Regional Government. |
| cornell data science course: A Grand Strategy for America Robert J. Art, 2013-02-01 The United States today is the most powerful nation in the world, perhaps even stronger than Rome was during its heyday. It is likely to remain the world's preeminent power for at least several decades to come. What behavior is appropriate for such a powerful state? To answer this question, Robert J. Art concentrates on grand strategy-the deployment of military power in both peace and war to support foreign policy goals. He first defines America's contemporary national interests and the specific threats they face, then identifies seven grand strategies that the United States might contemplate, examining each in relation to America's interests. The seven are: •dominion-forcibly trying to remake the world in America's own image; • global collective security-attempting to keep the peace everywhere; •regional collective security-confining peacekeeping efforts to Europe; • cooperative security-seeking to reduce the occurrence of war by limiting other states' offensive capabilities; • isolationism-withdrawing from all military involvement beyond U.S. borders; •containment-holding the line against aggressor states; and •selective engagement-choosing to prevent or to become involved only in those conflicts that pose a threat to the country's long-term interests. Art makes a strong case for selective engagement as the most desirable strategy for contemporary America. It is the one that seeks to forestall dangers, not simply react to them; that is politically viable, at home and abroad; and that protects all U.S. interests, both essential and desirable. Art concludes that selective engagement is not a strategy for all times, but it is the best grand strategy for these times. |
| cornell data science course: Machine Learning Kevin P. Murphy, 2012-08-24 A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students. |
| cornell data science course: Cracking the Data Science Interview Maverick Lin, 2019-12-17 Cracking the Data Science Interview is the first book that attempts to capture the essence of data science in a concise, compact, and clean manner. In a Cracking the Coding Interview style, Cracking the Data Science Interview first introduces the relevant concepts, then presents a series of interview questions to help you solidify your understanding and prepare you for your next interview. Topics include: - Necessary Prerequisites (statistics, probability, linear algebra, and computer science) - 18 Big Ideas in Data Science (such as Occam's Razor, Overfitting, Bias/Variance Tradeoff, Cloud Computing, and Curse of Dimensionality) - Data Wrangling (exploratory data analysis, feature engineering, data cleaning and visualization) - Machine Learning Models (such as k-NN, random forests, boosting, neural networks, k-means clustering, PCA, and more) - Reinforcement Learning (Q-Learning and Deep Q-Learning) - Non-Machine Learning Tools (graph theory, ARIMA, linear programming) - Case Studies (a look at what data science means at companies like Amazon and Uber) Maverick holds a bachelor's degree from the College of Engineering at Cornell University in operations research and information engineering (ORIE) and a minor in computer science. He is the author of the popular Data Science Cheatsheet and Data Engineering Cheatsheet on GCP and has previous experience in data science consulting for a Fortune 500 company focusing on fraud analytics. |
| cornell data science course: Enduring Alliance Timothy Andrews Sayle, 2019-04-15 Sayle's book is a remarkably well-documented history of the NATO alliance. This is a worthwhile addition to the growing literature on NATO and a foundation for understanding its current challenges and prospects.― Choice Born from necessity, the North Atlantic Treaty Organization (NATO) has always seemed on the verge of collapse. Even now, some seventy years after its inception, some consider its foundation uncertain and its structure weak. At this moment of incipient strategic crisis, Timothy A. Sayle offers a sweeping history of the most critical alliance in the post-World War II era. In Enduring Alliance, Sayle recounts how the western European powers, along with the United States and Canada, developed a treaty to prevent encroachments by the Soviet Union and to serve as a first defense in any future military conflict. As the growing and unruly hodgepodge of countries, councils, commands, and committees inflated NATO during the Cold War, Sayle shows that the work of executive leaders, high-level diplomats, and institutional functionaries within NATO kept the alliance alive and strong in the face of changing administrations, various crises, and the flux of geopolitical maneuverings. Resilience and flexibility have been the true hallmarks of NATO. As Enduring Alliance deftly shows, the history of NATO is organized around the balance of power, preponderant military forces, and plans for nuclear war. But it is also the history riven by generational change, the introduction of new approaches to conceiving international affairs, and the difficulty of diplomacy for democracies. As NATO celebrates its seventieth anniversary, the alliance once again faces challenges to its very existence even as it maintains its place firmly at the center of western hemisphere and global affairs. |
| cornell data science course: Plumb's Veterinary Drug Handbook Donald C. Plumb, 2018-02-21 Plumb’s Veterinary Drug Handbook, Ninth Edition updates the most complete, detailed, and trusted source of drug information relevant to veterinary medicine. Provides a fully updated edition of the classic veterinary drug handbook, with carefully curated dosages per indication for clear guidance on selecting a dose Features 16 new drugs Offers an authoritative, complete reference for detailed information about animal medication Designed to be used every day in the fast-paced veterinary setting Includes dosages for a wide range of species, including dogs, cats, exotic animals, and farm animals |
| cornell data science course: The Elements of Statistical Learning Trevor Hastie, Robert Tibshirani, Jerome Friedman, 2013-11-11 During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting. |
| cornell data science course: Authentic Happiness Martin Seligman, 2011-01-11 In this important, entertaining book, one of the world's most celebrated psychologists, Martin Seligman, asserts that happiness can be learned and cultivated, and that everyone has the power to inject real joy into their lives. In Authentic Happiness, he describes the 24 strengths and virtues unique to the human psyche. Each of us, it seems, has at least five of these attributes, and can build on them to identify and develop to our maximum potential. By incorporating these strengths - which include kindness, originality, humour, optimism, curiosity, enthusiasm and generosity -- into our everyday lives, he tells us, we can reach new levels of optimism, happiness and productivity. Authentic Happiness provides a variety of tests and unique assessment tools to enable readers to discover and deploy those strengths at work, in love and in raising children. By accessing the very best in ourselves, we can improve the world around us and achieve new and lasting levels of authentic contentment and joy. |
| cornell data science course: Essential Study Strategies Walter Pauk, 2000 This unique, concise book uses a conversational tone to encourage readers and students to immediately improve their learning experience. It provides inspiration and incentive for studying and achieving an education--along with easy-to-understand skills and strategies to become more effective in school. Strategies include setting goals, time management, concentration, and memory. Study skills coverage includes the Cornell Notetaking System and other formats, test taking, vocabulary building, classroom lectures, textbook assignments, and research papers. Two learning and study strategies inventories are provided to give meaningful information about the strengths and weaknesses of the student's study patterns in ten areas directly related to academic success. For students who want to improve their study skills and the quality of their education. |
| cornell data science course: Psychology for Sustainability Britain A. Scott, Elise L. Amel, Susan M. Koger, Christie M. Manning, 2015-07-24 Psychology for Sustainability, 4th Edition -- known as Psychology of Environmental Problems: Psychology for Sustainability in its previous edition -- applies psychological theory and research to so-called environmental problems, which actually result from human behavior that degrades natural systems. This upbeat, user-friendly edition represents a dramatic reorganization and includes a substantial amount of new content that will be useful to students and faculty in a variety of disciplines—and to people outside of academia, as well. The literature reviewed throughout the text is up-to-date, and reflects the burgeoning efforts of many in the behavioral sciences who are working to create a more sustainable society. The 4th Edition is organized in four sections. The first section provides a foundation by familiarizing readers with the current ecological crisis and its historical origins, and by offering a vision for a sustainable future.The next five chapters present psychological research methods, theory, and findings pertinent to understanding, and changing, unsustainable behavior. The third section addresses the reciprocal relationship between planetary and human wellbeing and the final chapter encourages readers to take what they have learned and apply it to move behavior in a sustainable direction. The book concludes with a variety of theoretically and empirically grounded ideas for how to face this challenging task with positivity, wisdom, and enthusiasm. This textbook may be used as a primary or secondary textbook in a wide range of courses on Ecological Psychology, Environmental Science, Sustainability Sciences, Environmental Education, and Social Marketing. It also provides a valuable resource for professional audiences of policymakers, legislators, and those working on sustainable communities. |
| cornell data science course: Hospitality Branding Chekitan S. Dev, 2012-11-01 In recent years the brand has moved squarely into the spotlight as the key to success in the hospitality industry. Business strategy once began with marketing and incorporated branding as one of its elements; today the brand drives marketing within the larger hospitality enterprise. Not only has it become the chief means of attracting customers, it has, more broadly, become the chief organizing principle for most hospitality organizations. The never-ending quest for market share follows trend after trend, from offering ever more elaborate and sophisticated amenities to the use of social media as a marketing tool—all driven by the preeminence of the brand. Chekitan S. Dev’s award-winning research has appeared in leading journals including Cornell Hospitality Quarterly, Journal of Marketing, and Harvard Business Review. He is the recipient of several major hospitality research and teaching awards. A former corporate executive with Oberoi Hotels & Resorts, he has served corporate, government, education, advisory, and private equity clients in more than forty countries as consultant, seminar leader, keynote speaker and expert witness. Hospitality Branding brings together the most important insights from the author’s many years of research and experience, all in a single, affordably priced volume (available in both print and eBook formats). Skillfully blending the knowledge of recent history, the wisdom of cutting-edge research, and promise of future trends, this book offers hospitality organizations the advice they need to survive and thrive in today’s competitive global business environment. |
| cornell data science course: Cornell Notebook Note taking Note taking system, Cornell Cornell Notes, 2017-09-27 Cornell Notebook 100 pages for note taking Based on Cornell Note Taking System Durable Matte Paperback with book binding 8.5 x 11 (21.59 x 27.94 cm) Note taking instructions included |
| cornell data science course: The Comstocks of Cornell Anna Botsford Comstock, 2019-03-15 The Comstocks of Cornell is the autobiography written by naturalist educator Anna Botsford Comstock about her life and her husband's, entomologist John Henry Comstock—both prominent figures in the scientific community and in Cornell University history. A first edition was published in 1953, but it omitted key Cornellians, historical anecdotes, and personal insights. Karen Penders St. Clair's twenty-first century edition returns Mrs. Comstock's voice to her book by rekeying her entire manuscript as she wrote it, and preserving the memories of the personal and professional lives of the Comstocks that she had originally intended to share. The book includes a complete epilogue of the Comstocks' last years and fills in gaps from the 1953 edition. Described as serious legacy work, the book is an essential part of Cornell University history and an important piece of Cornell University Press history. |
| cornell data science course: Patterns, Predictions, and Actions: Foundations of Machine Learning Moritz Hardt, Benjamin Recht, 2022-08-23 An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers |
| cornell data science course: Engineering Software as a Service Armando Fox, David A. Patterson, 2016 (NOTE: this Beta Edition may contain errors. See http://saasbook.info for details.) A one-semester college course in software engineering focusing on cloud computing, software as a service (SaaS), and Agile development using Extreme Programming (XP). This book is neither a step-by-step tutorial nor a reference book. Instead, our goal is to bring a diverse set of software engineering topics together into a single narrative, help readers understand the most important ideas through concrete examples and a learn-by-doing approach, and teach readers enough about each topic to get them started in the field. Courseware for doing the work in the book is available as a virtual machine image that can be downloaded or deployed in the cloud. A free MOOC (massively open online course) at saas-class.org follows the book's content and adds programming assignments and quizzes. See http://saasbook.info for details.(NOTE: this Beta Edition may contain errors. See http://saasbook.info for details.) A one-semester college course in software engineering focusing on cloud computing, software as a service (SaaS), and Agile development using Extreme Programming (XP). This book is neither a step-by-step tutorial nor a reference book. Instead, our goal is to bring a diverse set of software engineering topics together into a single narrative, help readers understand the most important ideas through concrete examples and a learn-by-doing approach, and teach readers enough about each topic to get them started in the field. Courseware for doing the work in the book is available as a virtual machine image that can be downloaded or deployed in the cloud. A free MOOC (massively open online course) at saas-class.org follows the book's content and adds programming assignments and quizzes. See http://saasbook.info for details. |
| cornell data science course: Probability And Statistics For Economists Yongmiao Hong, 2017-11-02 Probability and Statistics have been widely used in various fields of science, including economics. Like advanced calculus and linear algebra, probability and statistics are indispensable mathematical tools in economics. Statistical inference in economics, namely econometric analysis, plays a crucial methodological role in modern economics, particularly in empirical studies in economics.This textbook covers probability theory and statistical theory in a coherent framework that will be useful in graduate studies in economics, statistics and related fields. As a most important feature, this textbook emphasizes intuition, explanations and applications of probability and statistics from an economic perspective. |
| cornell data science course: Thinking at Every Desk: Four Simple Skills to Transform Your Classroom Derek Cabrera, Laura Colosi, 2012-09-10 Cutting-edge skills for twenty-first-century learners and educators. Designed to transform teaching practice, this book provides the tools to understand thinking patterns and how learning actually happens. It empowers teachers to structure learning in the most meaningful way, helping students explore new paths to knowledge. |
| cornell data science course: Vegan Bodybuilding and Fitness Robert Cheeke, 2011-06-10 One of the world's most recognized vegan bodybuilders presents a comprehensive guide to building a fit body on a plant-based diet. Author Robert Cheeke inspires people to develop magnificent bodies. His experience with diet, training, contest preparation and other facets of this sport make Vegan Bodybuilding & Fitness a fantastic resource for beginners and experienced athletes alike. Readers are provided with insight into the mental and physical aspects involved in becoming a successful bodybuilder. An overview of nutrients and how they function in the body, along with mass-building menus for training, show how to thrive as an athlete and bodybuilder on a vegan diet. Recommendations are given on how to create a successful training regimen that will yield the best results. Throughout the text the author's voice resonates with passion, dedication, and determination. From invaluable advice on how to find sponsorship and make bodybuilding a career to learning how to use bodybuilding for activism and outreach, readers find multi-leveled support for their lifestyle. A resource section is included for products, services and equipment that are completely vegan. Vegan Bodybuilding & Fitness leaves a lasting impact by providing tools for motivation and commitment for any area of life. |
| cornell data science course: Convex Optimization Sébastien Bubeck, 2015-11-12 This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. It begins with the fundamental theory of black-box optimization and proceeds to guide the reader through recent advances in structural optimization and stochastic optimization. The presentation of black-box optimization, strongly influenced by the seminal book by Nesterov, includes the analysis of cutting plane methods, as well as (accelerated) gradient descent schemes. Special attention is also given to non-Euclidean settings (relevant algorithms include Frank-Wolfe, mirror descent, and dual averaging), and discussing their relevance in machine learning. The text provides a gentle introduction to structural optimization with FISTA (to optimize a sum of a smooth and a simple non-smooth term), saddle-point mirror prox (Nemirovski's alternative to Nesterov's smoothing), and a concise description of interior point methods. In stochastic optimization it discusses stochastic gradient descent, mini-batches, random coordinate descent, and sublinear algorithms. It also briefly touches upon convex relaxation of combinatorial problems and the use of randomness to round solutions, as well as random walks based methods. |
| cornell data science course: I'll Keep You Close Jeska Verstegen, 2021-10-05 Jeska doesn't know why her mother keeps the curtains drawn so tightly every day. And what exactly is she trying to drown out when she floods the house with Mozart? What are they hiding from? When Jeska's grandmother accidentally calls her by a stranger's name, she seizes her first clue to uncovering her family's past, and hopefully to all that's gone unsaid. With the help of an old family photo album, her father's encyclopedia collection, and the unquestioning friendship of a stray cat, the silence begins to melt into frightening clarity: Jeska's family survived a terror that they’ve worked hard to keep secret all her life. And somehow, it has both nothing and everything to do with her, all at once. A true story of navigating generational trauma as a child, I'll Keep You Close is about what comes after disaster: how survivors move forward, what they bring with them when they do, and the promise of beginning again while always keeping the past close. |
在康奈尔大学 (Cornell University) 就读是种怎样的体验？ - 知乎
但这里就分享一个好玩的经历吧，这件事我觉得真心是Cornell这样的名校才能给我的，而且是我看完《阿拉伯的劳伦斯》后一直神往的地方，那就是我在读书期间获得了沙特阿拉伯政府全额奖 …
大家怎么看位于纽约市的 Cornell Tech（康奈尔科技校区）项目？
因为我在Cornell本部也读过，应该比较有发言权，我就来解释下这个事。Cornell一直因为它较偏僻的地理位置被诟病，所以Cornell长期以来都有在纽约的分校，而且分校和本部之间联系紧密。 …
硕士毕业论文是深度学习相关，需要自己做数据集，但我做出来的 …
盲审的话有两个点可以毙掉你的论文： （1）自己做的数据集。一般算法创新需要在公开数据集上测试效果，如果需要特殊数据集，应该先在公开数据集上证明自己方法的有效性，然后再在自 …
常春藤、25所新常春藤、公立常春藤都是哪些学校？ - 知乎
康奈尔大学（Cornell University）#18; 新常春藤（25所） 范德堡大学（Vanderbilt University）#14; 圣路易斯华盛顿大学（Washington University in St. Louis）#16; 莱斯大 …
如何评价英伟达发布的 Tesla V100 计算卡？ - 知乎
原文：Cornell University -> Cornell Virtual Workshop -> Understanding GPU Architecture -> GPU Example: Tesla V100. It's fine to have a general understanding of what graphics processing …
致久坐腰疼的年轻人——七年总结的办公久坐护腰指南
Oct 24, 2023 · 根据2:1的规律，每天仍有至少有6小时以上的坐姿时间，更何况996的老哥门，每天至少有8小时需要坐在椅子上。
在康奈尔大学 (Cornell University) 就读是种怎样的体验？ - 知乎
但这里就分享一个好玩的经历吧，这件事我觉得真心是Cornell这样的名校才能给我的，而且是我看完《阿拉伯的劳伦斯》后一直神往的地方，那就是我在读书期间获得了沙特阿拉伯政府全额奖学金参加了 …
大家怎么看位于纽约市的 Cornell Tech（康奈尔科技校区）项目？
因为我在Cornell本部也读过，应该比较有发言权，我就来解释下这个事。Cornell一直因为它较偏僻的地理位置被诟病，所以Cornell长期以来都有在纽约的分校，而且分校和本部之间联系紧密。除 …
硕士毕业论文是深度学习相关，需要自己做数据集，但我做出来的 …
盲审的话有两个点可以毙掉你的论文： （1）自己做的数据集。一般算法创新需要在公开数据集上测试效果，如果需要特殊数据集，应该先在公开数据集上证明自己方法的有效性，然后再在自己数据集上展 …
常春藤、25所新常春藤、公立常春藤都是哪些学校？ - 知乎
康奈尔大学（Cornell University）#18; 新常春藤（25所） 范德堡大学（Vanderbilt University）#14; 圣路易斯华盛顿大学（Washington University in St. Louis）#16; 莱斯大学（Rice University）#16; …
如何评价英伟达发布的 Tesla V100 计算卡？ - 知乎
原文：Cornell University -> Cornell Virtual Workshop -> Understanding GPU Architecture -> GPU Example: Tesla V100. It's fine to have a general understanding of what graphics processing units …
致久坐腰疼的年轻人——七年总结的办公久坐护腰指南
Oct 24, 2023 · 根据2:1的规律，每天仍有至少有6小时以上的坐姿时间，更何况996的老哥门，每天至少有8小时需要坐在椅子上。
