Автор: Langtangen Hans Petter Название: A Primer on Scientific Programming with Python ISBN: 3662498863 ISBN-13(EAN): 9783662498866 Издательство: Springer Рейтинг: Цена: 32600.00 T Наличие на складе: Есть Описание: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches 'Matlab-style' and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. … Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.Alex Small, IEEE, CiSE Vol. 14 (2), March?/April 2012 “This fourth edition is awonderful, inclusive textbook that covers pretty much everything one needs toknow to go from zero to fairly sophisticated scientific programming in Python…”Joan Horvath, Computing Reviews, March2015
Автор: Giuseppe Nicosia; Panos Pardalos Название: Learning and Intelligent Optimization ISBN: 3642449727 ISBN-13(EAN): 9783642449727 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the 7th International Conference on Learning and Optimization, LION 7, which was held in Catania, Italy, in January 2013. They explore the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems.
Автор: Sanjay Jain; R?mi Munos; Frank Stephan; Thomas Zeu Название: Algorithmic Learning Theory ISBN: 3642409342 ISBN-13(EAN): 9783642409349 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the 24th International Conference on Algorithmic Learning Theory, ALT 2013, held in Singapore in October 2013, and co-located with the 16th International Conference on Discovery Science, DS 2013.
Автор: Ton de Jong; L Sarti Название: Design and Production of Multimedia and Simulation-based Learning Material ISBN: 9401044066 ISBN-13(EAN): 9789401044066 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In the meanwhile an extension of the programme has resulted in 8 extensions of existing projects and 8 new projects, bringing the number of projects to 30, with a corresponding total budget of 99.
Автор: Frank Emmert-Streib; Matthias Dehmer Название: Information Theory and Statistical Learning ISBN: 1441946500 ISBN-13(EAN): 9781441946508 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.
Автор: Xi-Ren Cao Название: Stochastic Learning and Optimization ISBN: 144194222X ISBN-13(EAN): 9781441942227 Издательство: Springer Рейтинг: Цена: 172350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Performance optimization is vital in the design and operation of modern engineering systems. This book provides a unified framework based on a sensitivity point of view. It introduces new approaches and proposes new research topics.
Автор: Dialla Konat? Название: Mathematical Modeling, Simulation, Visualization and e-Learning ISBN: 3642093728 ISBN-13(EAN): 9783642093722 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book features articles written by some of the most prominent leading applied mathematicians as well as young and promising ones. The common objective of these articles is to present an important issue which is currently widely discussed in scientific investigation with major human, economic or ecological implications.
Автор: Michael M. Richter; Carl H. Smith; Rolf Wiehagen; Название: Algorithmic Learning Theory ISBN: 354065013X ISBN-13(EAN): 9783540650133 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A collection of papers from the 9th International Conference on Algorithmic Learning Theory. They are organized in sections on inductive logic programming and data mining, inductive inference, learning via queries, prediction algorithms, inductive logic programming and learning formal languages.
Автор: Laurent Miclet; Colin de la Higuera Название: Grammatical Inference: Learning Syntax from Sentences ISBN: 3540617787 ISBN-13(EAN): 9783540617785 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Constitutes the refereed proceedings of the Third International Colloquium on Grammatical Inference. The 25 papers are organized in sections on algebraic methods and algorithms, natural language and pattern recognition, inductive logic programming and operational issues.
Автор: Danish Haroon Название: Python Machine Learning Case Studies ISBN: 1484228227 ISBN-13(EAN): 9781484228227 Издательство: Springer Рейтинг: Цена: 35390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You'll see machine learning techniques that you can use to support your products and services. Moreover you'll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs. By taking a step-by-step approach to coding in Python you'll be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems. What You Will Learn
Gain insights into machine learning concepts
Work on real-world applications of machine learning
Learn concepts of model selection and optimization
Get a hands-on overview of Python from a machine learning point of view
Who This Book Is For Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.
Автор: Hill Название: Learning Scientific Programming with Python ISBN: 1107075416 ISBN-13(EAN): 9781107075412 Издательство: Cambridge Academ Рейтинг: Цена: 91860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Learn to master basic programming tasks from scratch with real-life scientific examples drawn from many different areas of science and engineering. This complete introduction to using Python teaches Numpy, SciPy and Matplotlib libraries and is supported by extensive online resources to provide a targeted package for students and researchers.
Автор: Dipanjan Sarkar; Raghav Bali; Tushar Sharma Название: Practical Machine Learning with Python ISBN: 1484232062 ISBN-13(EAN): 9781484232064 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully.
Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code.
Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered.
Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment.
Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem.
Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today
What You'll Learn
Execute end-to-end machine learning projects and systems
Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks
Review case studies depicting applications of machine learning and deep learning on diverse domains and industries
Apply a wide range of machine learning models including regression, classification, and clustering.
Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning.
Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students
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