Machine Learning for Asset Managers, Marcos Lopez de Prado
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 9978.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Автор: Christopher M. Bishop Название: Pattern Recognition and Machine Learning ISBN: 0387310738 ISBN-13(EAN): 9780387310732 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Автор: Darren Cook Название: Practical Machine Learning with H2O ISBN: 149196460X ISBN-13(EAN): 9781491964606 Издательство: Wiley Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.
Автор: Campbell John Y. Название: Financial Decisions and Markets: A Course in Asset Pricing ISBN: 0691160805 ISBN-13(EAN): 9780691160801 Издательство: Wiley Рейтинг: Цена: 12672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
From the field's leading authority, the most authoritative and comprehensive advanced-level textbook on asset pricing
Financial Decisions and Markets is a graduate-level textbook that provides a broad overview of the field of asset pricing. John Campbell, one of the field's most respected authorities, introduces students to leading theories of portfolio choice, their implications for asset prices, and empirical patterns of risk and return in financial markets. Campbell emphasizes the interplay of theory and evidence, as theorists respond to empirical puzzles by developing models with new testable implications. Increasingly these models make predictions not only about asset prices but also about investors' financial positions, and they often draw on insights from behavioral economics.
After a careful introduction to single-period models, Campbell develops multiperiod models with time-varying discount rates, reviews the leading approaches to consumption-based asset pricing, and integrates the study of equities and fixed-income securities. He discusses models with heterogeneous agents who use financial markets to share their risks, but also may speculate against one another on the basis of different beliefs or private information. Campbell takes a broad view of the field, linking asset pricing to related areas, including financial econometrics, household finance, and macroeconomics. The textbook works in discrete time throughout, and does not require stochastic calculus. Problems are provided at the end of each chapter to challenge students to develop their understanding of the main issues in financial economics.
The most comprehensive and balanced textbook on asset pricing available, Financial Decisions and Marketswill be an essential resource for all graduate students in finance and related fields.
Integrated treatment of asset pricing theory and empirical evidence
Emphasis on investors' decisions
Broad view linking the field to areas including financial econometrics, household finance, and macroeconomics
Topics treated in discrete time, with no requirement for stochastic calculus
Solutions manual for problems available to professors
Автор: Raschka, Sebastian Mirjalili, Vahid Название: Python machine learning - ISBN: 1787125939 ISBN-13(EAN): 9781787125933 Издательство: Неизвестно Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you`ll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.
Описание: Understanding the Ground Rules for the Global EconomyIn this revised and updated edition of A Concise Guide to Macroeconomics, David A. Moss draws on his years of teaching at Harvard Business School to explain important macro concepts using clear and engaging language. This guidebook covers the essentials of macroeconomics and examines, in a simple and intuitive way, the core ideas of output, money, and expectations.
Early chapters leave you with an understanding of everything from fiscal policy and central banking to business cycles and international trade. Later chapters provide a brief monetary history of the United States as well as the basics of macroeconomic accounting. You'll learn why countries trade, why exchange rates move, and what makes an economy grow.
Moss's detailed examples will arm you with a clear picture of how the economy works and how key variables impact business and will equip you to anticipate and respond to major macroeconomic events, such as a sudden depreciation of the real exchange rate or a steep hike in the federal funds rate. Read this book from start to finish for a complete overview of macroeconomics, or use it as a reference when you're confronted with specific challenges, like the need to make sense of monetary policy or to read a balance of payments statement. Either way, you'll come away with a broad understanding of the subject and its key pieces, and you'll be empowered to make smarter business decisions.
Описание: This groundbreaking new book answers to an essential question: why is it that a fund client selects, or an investment consultant recommends, one asset manager over another when the two are, on paper at least, very similar?
Описание: This groundbreaking new book answers an essential question: why is it that a fund client selects, or an investment consultant recommends, one asset manager over another when the two are, on paper at least, very similar?
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Shalev-Shwartz Название: Understanding Machine Learning ISBN: 1107057132 ISBN-13(EAN): 9781107057135 Издательство: Cambridge Academ Рейтинг: Цена: 11194.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the `hows` and `whys` of machine-learning algorithms, making the field accessible to both students and practitioners.
Описание: Recognize Wall Street tactics for what they are, and make smarter decisions with your money Wall Street Potholes shares insights into the money management industry, revealing the shady practices that benefit the salesman far more than the client.
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