Foundations of data science with python, Shea, John M.
Автор: David Jamieson Bolder Название: Credit-Risk Modelling/Книга: Дэвид Джеймисон Болдер Моделирование кредитного риска ISBN: 3030069001 ISBN-13(EAN): 9783030069001 Издательство: Springer Рейтинг: Цена: 55050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.
Автор: Bolder David Jamieson Название: Credit-Risk Modelling: Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python ISBN: 3319946870 ISBN-13(EAN): 9783319946870 Издательство: Springer Рейтинг: Цена: 38100.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study.
Автор: Guido Sarah Название: Introduction to Machine Learning with Python ISBN: 1449369413 ISBN-13(EAN): 9781449369415 Издательство: Wiley Рейтинг: Цена: 63350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.
Название: Music data analysis ISBN: 0367872811 ISBN-13(EAN): 9780367872816 Издательство: Taylor&Francis Рейтинг: Цена: 64300.00 T Наличие на складе: Нет в наличии. Описание: This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user
Автор: Weihs, Claus , Mersmann, Olaf , Ligges, Uwe Название: Foundations of Statistical Algorithms ISBN: 0367379090 ISBN-13(EAN): 9780367379094 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Невозможна поставка. Описание:
A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundationsof Statistical Algorithms: With References to R Packages reviews the historical development of basic algorithms to illuminate the evolution of today's more powerful statistical algorithms. It emphasizes recurring themes in all statistical algorithms, including computation, assessment and verification, iteration, intuition, randomness, repetition and parallelization, and scalability. Unique in scope, the book reviews the upcoming challenge of scaling many of the established techniques to very large data sets and delves into systematic verification by demonstrating how to derive general classes of worst case inputs and emphasizing the importance of testing over a large number of different inputs.
Broadly accessible, the book offers examples, exercises, and selected solutions in each chapter as well as access to a supplementary website. After working through the material covered in the book, readers should not only understand current algorithms but also gain a deeper understanding of how algorithms are constructed, how to evaluate new algorithms, which recurring principles are used to tackle some of the tough problems statistical programmers face, and how to take an idea for a new method and turn it into something practically useful.
Автор: Murtagh, Fionn Название: Data science foundations ISBN: 0367657759 ISBN-13(EAN): 9780367657758 Издательство: Taylor&Francis Рейтинг: Цена: 50010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects.
Автор: Ahlswede Alexander, Ahlswede Rudolf, Althцfer Ingo Название: Hiding Data - Selected Topics: Rudolf Ahlswede`s Lectures on Information Theory 3 ISBN: 3319810553 ISBN-13(EAN): 9783319810553 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Devoted to information security, this volume begins with a short course on cryptography, mainly basedon lectures given by Rudolf Ahlswede at the University of Bielefeld in the mid1990s.
Автор: Shikhman, Vladimir Muller, David Название: Mathematical foundations of big data analytics ISBN: 3662625202 ISBN-13(EAN): 9783662625200 Издательство: Springer Рейтинг: Цена: 32600.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made.
Автор: Kao Chiang Название: Network Data Envelopment Analysis: Foundations and Extensions ISBN: 3319811045 ISBN-13(EAN): 9783319811048 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduction.- Output-Input Ratio Efficiency Measures.- Distance Function Efficiency Measures.- Slacks-based Efficiency Measures.- Efficiency Measurement in Special Production Stages.- Special Types of Input and Output Factors.- Special Types of Data.- Changes of Efficiency over Time.- Basic Ideas in Efficiency Measurement for Network Systems.- Basic Two-stage Systems.- General Two-stage Systems.- General Multi-stage Systems.- Parallel Systems.- Hierarchical Systems.- Assembly and Disassembly Systems.- Mixed Systems.- Dynamic Systems.- Epilogue.
Автор: Kauermann Gцran, Kьchenhoff Helmut, Heumann Christian Название: Statistical Foundations, Reasoning and Inference: For Science and Data Science ISBN: 3030698262 ISBN-13(EAN): 9783030698263 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science.
Автор: Renz, Malte (division Of Gynecologic Oncology, Stanford University School Of Medicine, Usa) Diver, Elisabeth (division Of Gynecologic Oncology, Stanfo Название: Foundations of quantitative finance, book i: measure spaces and measurable functions ISBN: 1032207221 ISBN-13(EAN): 9781032207223 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Нет в наличии. Описание: The book provides a snapshot of practices used by contemporary designers, researchers, and artists who create objects, spaces, and experiences imbued with data. They draw from a range of domains and traditions, and represent a fascinating, inspiring, and revealing cross-section of contemporary maker and data culture.
