STEM Problems with Mathcad and Python, Stevens, Alan
Автор: Jesъs Sofнa de, Martinez Dayrene Название: Applied Computational Thinking with Python: Design algorithmic solutions for complex and challenging real-world problems ISBN: 1839219432 ISBN-13(EAN): 9781839219436 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Applied Computational Thinking with Python provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time. Developers working with Python will be able to put their knowledge to work with this practical guide using the computational thinking method for problem-solving.
Автор: Knight, Vincent (cardiff University) Palmer, Geraint (cardiff University) Название: Applied mathematics with open-source software ISBN: 0367339986 ISBN-13(EAN): 9780367339982 Издательство: Taylor&Francis Рейтинг: Цена: 45930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics.Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a number of published references.
Автор: Lasley, Paul Leistritz, F. Larry Lobao, Linda M. Meyer, Katherine Barnard, Freddie L. Biere, Arlo Fellows, Jackie Hobbs, Daryl Johnson, Bruce Olson, K Название: Who will provide? the changing role of religion in american social welfare ISBN: 0367348683 ISBN-13(EAN): 9780367348687 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics.Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a number of published references.
Автор: Maxfield, Brent Название: Essential Mathcad For Engineering, Science, And Math Ise ISBN: 0123748461 ISBN-13(EAN): 9780123748461 Издательство: Elsevier Science Рейтинг: Цена: 43780.00 T Наличие на складе: Нет в наличии. Описание: Introduces the powerful functions and features of the software and teaches how to apply these to create comprehensive calculations for any quantitative subject. This title demonstrates how other software, such as Excel spreadsheets, can be incorporated effectively. It is suitable for professional engineers and engineering, and science students.
Автор: Wessel Badenhorst Название: Practical Python Design Patterns ISBN: 1484226798 ISBN-13(EAN): 9781484226797 Издательство: Springer Рейтинг: Цена: 32600.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Become a better, more productive programmer through a series of projects that will help you deeply understand and master each of the design patterns covered.
Автор: Havill, Jessen Название: Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming ISBN: 036747249X ISBN-13(EAN): 9780367472498 Издательство: Taylor&Francis Рейтинг: Цена: 80630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines.
Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models,
and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations.
Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study.
What You Will Learn
Build basic Python-based artificial intelligence (AI) applications Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suiteCreate several types of projects using Python and Google OR-Tools
Who This Book Is For
Developers and students who already have prior experience in Python coding. Some prior mathematical experience or comfort level may be helpful as well.
Автор: Hodeghatta Название: Practical Business Analytics Using R and Python ISBN: 1484287533 ISBN-13(EAN): 9781484287538 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You’ll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing. Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics. What You Will Learn * Master the mathematical foundations required for business analytics * Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task * Use R and Python to develop descriptive models, predictive models, and optimize models * Interpret and recommend actions based on analytical model outcomes Who This Book Is For Software professionals and developers, managers, and executives who want to understand and learn the fundamentals of analytics using R and Python.
Автор: Chatterjee Chanchal Название: Adaptive Machine Learning Algorithms with Python: Solve Data Analytics and Machine Learning Problems on Edge Devices ISBN: 1484280164 ISBN-13(EAN): 9781484280164 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter 1. Introducing Data Representation FeaturesSet the context for the reader with important data representation features, present the need for adaptive algorithms to compute them and demonstrate how these algorithms are important in multiple disciplines. Additionally, discuss a common methodology adopted to derive all our algorithms.Sub-topics: 1. Data representation features2. Computational models for time-varying multi-dimensional data3. Multi-disciplinary origin of adaptive algorithms4. Common Methodology for Derivations of Algorithms5. Outline of The Book Chapter 2. General Theories and NotationsIntroduce the reader to types of data in real-world streaming applications, discuss practical use cases and derive adaptive algorithms for mean, normalized mean, median, and covariances. Support the results with experiments on real data.Sub-topics: 1. Introduction2. Stationary and Non-Stationary Sequences3. Use Cases for Algorithms Covered in this Chapter 4. Adaptive Mean and Covariance of Nonstationary Sequences5. Adaptive Covariance and Inverses6. Adaptive Normalized Mean Algorithm7. Adaptive Median Algorithm8. Experimental Results Chapter 3. Square Root and Inverse Square RootIntroduce readers to practical applications of square roots and inverse square roots of streaming data matrices, then present algorithms to compute them. Support the algorithms with real data.Sub-topics: 1. Introduction and Use Cases2. Adaptive Square Root Algorithms3. Adaptive Inverse Square Root Algorithms4. Experimental Results Chapter 4. First Principal EigenvectorIntroduce the reader to adaptive computation of first principal component of streaming data, discuss the use cases with examples, derive ten algorithms with the common methodology adopted here. Demonstrate the algorithms with real-world non-stationary streaming data examples.Sub-topics: 1. Introduction and Use Cases2. Algorithms and Objective Functions3. OJA Algorithm4. RQ, OJAN, and LUO Algorithms5. IT and XU Algorithms6. Penalty Function Algorithm 7. Augmented Lagrangian Algorithms8. Summary of Algorithms9. Experimental Results Chapter 5. Principal and Minor EigenvectorsIntroduce the reader to adaptive computation of all principal components, discuss powerful use cases with examples, derive 21 adaptive algorithms and demonstrate the algorithms on real-world time-varying data.Sub-topics: 1. Introduction and Use Cases2. Algorithms and Objective Functions3. OJA Algorithms4. XU Algorithms5. PF Algorithms6. AL1 Algorithms7. AL2 Algorithms8. IT Algorithms9. RQ Algorithms10. Summary of Adaptive Eigenvector Algorithms11. Experimental Results Chapter 6. Accelerated Computation eigenvectorsIntroduce the reader to methods to speed up the adaptive algorithms presented in this book. Help the reader speed up a few algorithms and demonstrate their usefulness and acceleration on real-world stationery and non-stationary data.Sub-topics: 1. Introduction2. Gradient Descent Algorithm3. Steepest Descent Algorithm4. Conjugate Direction Algorithm5. Newton-Raphson Algorithm6. Experimental Results Chapter 7. Generalized EigenvectorsIntroduce the reader to the adaptive computation of generalized eigenvectors of streaming data matrices in real-time applications. Dis
Автор: Ochkov, Valery Название: 25 problems for stem education ISBN: 1032174625 ISBN-13(EAN): 9781032174624 Издательство: Taylor&Francis Рейтинг: Цена: 39800.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 25 Problems for STEM Education introduces a new and emerging course for undergraduate STEM programs called Physical-Mathematical Informatics. This course corresponds with the new direction in education called STE(A)M (Science, Technology, Engineering, [Art] and Mathematics).
Автор: Havill Jessen Название: Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming ISBN: 0367613352 ISBN-13(EAN): 9780367613358 Издательство: Taylor&Francis Рейтинг: Цена: 183750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines.
Автор: Ochkov, Valery F. Название: 25 problems for stem education ISBN: 0367345250 ISBN-13(EAN): 9780367345259 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Невозможна поставка. Описание: 25 Problems for STEM Education introduces a new and emerging course for undergraduate STEM programs called Physical-Mathematical Informatics. This course corresponds with the new direction in education called STE(A)M (Science, Technology, Engineering, [Art] and Mathematics).
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