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
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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
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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
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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.

Автор: Agresti, Alan,
Название: Foundations of statistics for data scientists :
ISBN: 0367748452 ISBN-13(EAN): 9780367748456
Издательство: Taylor&Francis
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Цена: 91860.00 T
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Описание: This book shows the elements of statistical science that are highly relevant for students who plan to become data scientists. However, most of the content focuses on the statistical methods and the theory behind them, rather than on data science.

Автор: Shea, John M.
Название: Foundations of data science with python
ISBN: 1032350423 ISBN-13(EAN): 9781032350424
Издательство: Taylor&Francis
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Цена: 75530.00 T
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Автор: Bower Tim, Goerzen John, Rhodes Brandon
Название: Foundations of Python 3 Network Programming, Second Edition
ISBN: 1430230037 ISBN-13(EAN): 9781430230038
Издательство: Springer
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Цена: 46110.00 T
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Описание: Introduction You have chosen an exciting moment in computing history to embark on a study of network programming. Machine room networks can carry data at speeds comparable to those at which machines access their own memory, and broadband now reaches hundreds of millions of homes worldwide. Many casual computer users spend their entire digital lives speaking exclusively to network services; they are only vaguely aware that their computer is even capable of running local applications. This is also a moment when, after 20 solid years of growth and improvement, interest in Python really seems to be taking off. This is different from the trajectory of other popular languages, many of which experience their heyday and go into decline long before the threshold of their third decade. The Python community is not only strong and growing, but its members seem to have a much better feel for the language itself than they did a decade ago. The advice we can share with new Python programmers about how to test, write, and structure applications is vastly more mature than what passed for Pythonic design a mere decade ago.

Автор: Ashley, W. David Krause, Andrew
Название: Foundations of pygtk development
ISBN: 1484241789 ISBN-13(EAN): 9781484241783
Издательство: Springer
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Цена: 55890.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn how to develop portable GUI programs to run on multiple operating systems. Revised and updated from the popular original, with a full set of new examples in Python and using PyGTK, this book provides all the information you'll need to write easy or complex GUI applications, offering one source of knowledge and best practices for user interface creation.Foundations of PyGTK Development presents numerous real-life examples that you can immediately put to use in your own applications. It begins with an overview of key topics such as widget choice, placement, and behavior, before moving on to more advanced issues. Building on your familiarity with Python, the book delves into new topics such as object inheritance early on to allow for a complete understanding of code examples later. What You'll LearnWork with layout containers including boxes, tables, grid, and panesUse the Application and ApplicationWindow classes as the base for your PyGTK applicationManage dialogs to give general information, error messages, or warnings to the userIncorporate styles, images, and the clipboard within your applicationsWho This Book is ForExperienced Python programmers or DevOps administrators tasked with developing or maintaining user interfaces.

Автор: Rhodes Brandon
Название: Foundations of Python Network Programming
ISBN: 1430258543 ISBN-13(EAN): 9781430258544
Издательство: Springer
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Цена: 35360.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

1. Introduction to Client/Server Networking
2. UDP
3. TCP
4. Socket Names and DNS
5. Network Data and Network Errors
6. TLS and SSL
7. Server Architecture
8. Caches, Message Queues, and Map-Reduce
9. HTTP
10. Screen Scraping
11. Web Applications
12. E-mail Composition and Decoding
13. SMTP
14. POP
15. IMAP
16. Other technologies: Telnet, SSH, and FTP
17. RPC
18. System Administration

Автор: Kolaczyk Eric D
Название: Topics at the Frontier of Statistics and Network Analysis
ISBN: 1108407129 ISBN-13(EAN): 9781108407120
Издательство: Cambridge Academ
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Цена: 31670.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This snapshot of the current frontier of statistics and network analysis focuses on the foundational topics of modeling, sampling, and design. Primarily for graduate students and researchers in statistics and closely related fields, emphasis is not only on what has been done, but on what remains to be done.

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
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Цена: 74530.00 T
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Описание: This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science.

Название: Music Data Analysis
ISBN: 1498719562 ISBN-13(EAN): 9781498719568
Издательство: Taylor&Francis
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Цена: 70430.00 T
Наличие на складе: Нет в наличии.

Автор: Weihs, Claus , Mersmann, Olaf , Ligges, Uwe
Название: Foundations of Statistical Algorithms
ISBN: 0367379090 ISBN-13(EAN): 9780367379094
Издательство: Taylor&Francis
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Цена: 65320.00 T
Наличие на складе: Невозможна поставка.
Описание:

A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundations of 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.