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Machine Learning Under a Modern Optimization Lens, Dimitris Bertsimas


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Автор: Dimitris Bertsimas   (Димитрис Бертсимас)
Название:  Machine Learning Under a Modern Optimization Lens
Перевод названия: Димитрис Бертсимас: Машинное обучение с точки зрения современной оптимизации
ISBN: 9781733788502
Издательство: Amazon Internet
Классификация: ISBN-10: 1733788506
Вес: 0.00 кг.
Дата издания: 1 Jan. 2019
Поставляется из: Англии


Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 11878.00 р.
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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.

Dreams Come to Life (Bendy and the Ink Machine, Book 1)

Автор: Kress Adrienne
Название: Dreams Come to Life (Bendy and the Ink Machine, Book 1)
ISBN: 1338343947 ISBN-13(EAN): 9781338343946
Издательство: Scholastic
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Цена: 1527.00 р.
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Описание: The official spine-tingling prequel novel based on the hit horrorvideo game, Bendy and the Ink Machine!

Joey Drew Studios Employee Handbook (Bendy and the Ink Machine)

Автор: Scholastic
Название: Joey Drew Studios Employee Handbook (Bendy and the Ink Machine)
ISBN: 1338343920 ISBN-13(EAN): 9781338343922
Издательство: Scholastic
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Цена: 1762.00 р.
Наличие на складе: Нет в наличии.

Описание: Bendy and the Ink Machine is a horror game that begins in the fardays of animation`s past and ends in a very dark future. Explorethe world with this creepy in-world handbook!

Introduction to Machine Learning with Python

Автор: Guido Sarah
Название: Introduction to Machine Learning with Python
ISBN: 1449369413 ISBN-13(EAN): 9781449369415
Издательство: Wiley
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Цена: 9502.00 р.
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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.

Numerical Optimization

Автор: Nocedal, Jorge.
Название: Numerical Optimization
ISBN: 0387303030 ISBN-13(EAN): 9780387303031
Издательство: Springer
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Цена: 10662.00 р.
Наличие на складе: Заказано в издательстве.

Описание: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

Advances In Combinatorial Optimization: Linear Programming Formulations Of The Traveling Salesman And Other Hard Combinatorial Optimization Problems

Автор: Diaby Moustapha Et Al
Название: Advances In Combinatorial Optimization: Linear Programming Formulations Of The Traveling Salesman And Other Hard Combinatorial Optimization Problems
ISBN: 9814704873 ISBN-13(EAN): 9789814704878
Издательство: World Scientific Publishing
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Цена: 13939.00 р.
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Описание:

Combinational optimization (CO) is a topic in applied mathematics, decision science and computer science that consists of finding the best solution from a non-exhaustive search. CO is related to disciplines such as computational complexity theory and algorithm theory, and has important applications in fields such as operations research/management science, artificial intelligence, machine learning, and software engineering.

Advances in Combinatorial Optimization presents a generalized framework for formulating hard combinatorial optimization problems (COPs) as polynomial sized linear programs. Though developed based on the 'traveling salesman problem' (TSP), the framework allows for the formulating of many of the well-known NP-Complete COPs directly (without the need to reduce them to other COPs) as linear programs, and demonstrates the same for three other problems (e.g. the 'vertex coloring problem' (VCP)). This work also represents a proof of the equality of the complexity classes "P" (polynomial time) and "NP" (nondeterministic polynomial time), and makes a contribution to the theory and application of 'extended formulations' (EFs).

On a whole, Advances in Combinatorial Optimization offers new modeling and solution perspectives which will be useful to professionals, graduate students and researchers who are either involved in routing, scheduling and sequencing decision-making in particular, or in dealing with the theory of computing in general.

Machine Learning, Optimization, and Big Data

Автор: Pardalos
Название: Machine Learning, Optimization, and Big Data
ISBN: 3319514687 ISBN-13(EAN): 9783319514680
Издательство: Springer
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Цена: 9224.00 р.
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Описание: This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions.

Machine Learning, Optimization, and Big Data

Автор: Panos Pardalos; Mario Pavone; Giovanni Maria Farin
Название: Machine Learning, Optimization, and Big Data
ISBN: 3319279254 ISBN-13(EAN): 9783319279251
Издательство: Springer
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Цена: 7826.00 р.
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Описание: This bookconstitutes revised selected papers from the First International Workshop onMachine Learning, Optimization, and Big Data, MOD 2015, held in Taormina, Sicily,Italy, in July 2015. The 32papers presented in this volume were carefully reviewed and selected from 73submissions.

Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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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.

Python machine learning -

Автор: Raschka, Sebastian Mirjalili, Vahid
Название: Python machine learning -
ISBN: 1787125939 ISBN-13(EAN): 9781787125933
Издательство: Неизвестно
Цена: 8091.00 р.
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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.

Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
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Описание:

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
Optimization of Power System Operation 2e

Автор: Jizhong Zhu
Название: Optimization of Power System Operation 2e
ISBN: 1118854152 ISBN-13(EAN): 9781118854150
Издательство: Wiley
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Цена: 19317.00 р.
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Описание: Optimization of Power System Operation, 2 nd Edition, offers a practical, hands-on guide to theoretical developments and to the application of advanced optimization methods to realistic electric power engineering problems.


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