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Author: José Luis Prieto Morlanés
Publisher: Ra-Ma Editorial
ISBN: 8410181010
Category : Computers
Languages : es
Pages : 352
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Book Description
Con esta obra el lector emprenderá un emocionante viaje a través del mundo de las matemáticas y la visualización de datos utilizando el poderoso lenguaje de programación Python. Este libro no solo ofrece una introducción accesible a los conceptos matemáticos fundamentales, sino que también proporciona las herramientas necesarias para aplicar estos conocimientos a través de la programación. A lo largo de sus páginas, el autor guía al lector en un recorrido interactivo que abarca desde los conceptos básicos de la trigonometría y el cálculo hasta técnicas avanzadas de visualización de datos. Utilizando bibliotecas de Python como NumPy y Matplotlib, los lectores aprenderán a crear gráficos impresionantes y a manipular conjuntos de datos de manera efectiva. Cada capítulo presenta nuevos conceptos matemáticos junto con ejemplos de código prácticos. Desde la creación de gráficos de funciones simples hasta la visualización de conjuntos de datos multidimensionales, este libro proporciona una base sólida para aquellos interesados en explorar las matemáticas desde una perspectiva computacional. Ya sea el lector sea un principiante en programación o un matemático experimentado en busca de nuevas formas de visualizar y analizar datos, este libro ofrece una experiencia educativa enriquecedora y estimulante que abrirá nuevas puertas hacia la comprensión y la exploración del mundo de las matemáticas con Python. El código descrito en el libro se podrá descargar accediendo a la ficha del libro en www.ra-ma.es.
Author: José Luis Prieto Morlanés
Publisher: Ra-Ma Editorial
ISBN: 8410181010
Category : Computers
Languages : es
Pages : 352
Get Book Here
Book Description
Con esta obra el lector emprenderá un emocionante viaje a través del mundo de las matemáticas y la visualización de datos utilizando el poderoso lenguaje de programación Python. Este libro no solo ofrece una introducción accesible a los conceptos matemáticos fundamentales, sino que también proporciona las herramientas necesarias para aplicar estos conocimientos a través de la programación. A lo largo de sus páginas, el autor guía al lector en un recorrido interactivo que abarca desde los conceptos básicos de la trigonometría y el cálculo hasta técnicas avanzadas de visualización de datos. Utilizando bibliotecas de Python como NumPy y Matplotlib, los lectores aprenderán a crear gráficos impresionantes y a manipular conjuntos de datos de manera efectiva. Cada capítulo presenta nuevos conceptos matemáticos junto con ejemplos de código prácticos. Desde la creación de gráficos de funciones simples hasta la visualización de conjuntos de datos multidimensionales, este libro proporciona una base sólida para aquellos interesados en explorar las matemáticas desde una perspectiva computacional. Ya sea el lector sea un principiante en programación o un matemático experimentado en busca de nuevas formas de visualizar y analizar datos, este libro ofrece una experiencia educativa enriquecedora y estimulante que abrirá nuevas puertas hacia la comprensión y la exploración del mundo de las matemáticas con Python. El código descrito en el libro se podrá descargar accediendo a la ficha del libro en www.ra-ma.es.
Author:
Publisher:
ISBN: 9788410181694
Category :
Languages : es
Pages : 0
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Book Description
Author: Bas P. Harenslak
Publisher: Simon and Schuster
ISBN: 1617296902
Category : Computers
Languages : en
Pages : 478
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Book Description
For DevOps, data engineers, machine learning engineers, and sysadmins with intermediate Python skills"--Back cover.
Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1000708039
Category : Mathematics
Languages : en
Pages : 836
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Book Description
Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Author: Sandeep Nagar
Publisher: Apress
ISBN: 1484231716
Category : Computers
Languages : en
Pages : 359
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Book Description
Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or Stata combined with the speed, capacity, and performance of C, C++, or Java. You’ll learn the OOP principles required to get you started, then how to do basic mathematics with Julia. Other core functionality of Julia that you’ll cover, includes working with complex numbers, rational and irrational numbers, rings, and fields. Beginning Julia Programming takes you beyond these basics to harness Julia’s powerful features for mathematical functions in Julia, arrays for matrix operations, plotting, and more. Along the way, you also learn how to manage strings, write functions, work with control flows, and carry out I/O to implement and leverage the mathematics needed for your data science and analysis projects. "Julia walks like Python and runs like C". This phrase explains why Julia is quickly growing as the most favored option for data analytics and numerical computation. After reading and using this book, you'll have the essential knowledge and skills to build your first Julia-based application. What You'll Learn Obtain core skills in Julia Apply Julia in engineering and science applications Work with mathematical functions in Julia Use arrays, strings, functions, control flow, and I/O in Julia Carry out plotting and display basic graphics Who This Book Is For Those who are new to Julia; experienced users may also find this helpful as a reference.
Author: Waldemar Karwowski
Publisher: Springer Nature
ISBN: 3030582825
Category : Technology & Engineering
Languages : en
Pages : 385
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Book Description
This book focuses on novel design and systems engineering approaches, including theories and best practices, for promoting a better integration of people and engineering systems. It covers a range of innovative topics related to: development of human-centered systems; interface design and human-computer interaction; usability and user experience; innovative materials in design and manufacturing; biomechanics and physical rehabilitation, as well as safety engineering and systems complexity. The book, which gathers selected papers presented at the 3rd International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2020), held on September 22-24, 2020, at Juraj Dobrila University of Pula, in Pula, Croatia, provides researchers and practitioners with a snapshot of the state-of-the-art and current challenges in the field of human systems engineering and design.
Author: Morton J. Canty
Publisher: CRC Press
ISBN: 1466570377
Category : Mathematics
Languages : en
Pages : 575
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Book Description
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Author: Stephen Wolfram
Publisher:
ISBN: 9780201515022
Category :
Languages : en
Pages : 996
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Book Description
Author: Michael Lewis
Publisher: W. W. Norton & Company
ISBN: 0393066231
Category : Sports & Recreation
Languages : en
Pages : 337
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Book Description
Michael Lewis’s instant classic may be “the most influential book on sports ever written” (People), but “you need know absolutely nothing about baseball to appreciate the wit, snap, economy and incisiveness of [Lewis’s] thoughts about it” (Janet Maslin, New York Times). One of GQ's 50 Best Books of Literary Journalism of the 21st Century Just before the 2002 season opens, the Oakland Athletics must relinquish its three most prominent (and expensive) players and is written off by just about everyone—but then comes roaring back to challenge the American League record for consecutive wins. How did one of the poorest teams in baseball win so many games? In a quest to discover the answer, Michael Lewis delivers not only “the single most influential baseball book ever” (Rob Neyer, Slate) but also what “may be the best book ever written on business” (Weekly Standard). Lewis first looks to all the logical places—the front offices of major league teams, the coaches, the minds of brilliant players—but discovers the real jackpot is a cache of numbers?numbers!?collected over the years by a strange brotherhood of amateur baseball enthusiasts: software engineers, statisticians, Wall Street analysts, lawyers, and physics professors. What these numbers prove is that the traditional yardsticks of success for players and teams are fatally flawed. Even the box score misleads us by ignoring the crucial importance of the humble base-on-balls. This information had been around for years, and nobody inside Major League Baseball paid it any mind. And then came Billy Beane, general manager of the Oakland Athletics. He paid attention to those numbers?with the second-lowest payroll in baseball at his disposal he had to?to conduct an astonishing experiment in finding and fielding a team that nobody else wanted. In a narrative full of fabulous characters and brilliant excursions into the unexpected, Michael Lewis shows us how and why the new baseball knowledge works. He also sets up a sly and hilarious morality tale: Big Money, like Goliath, is always supposed to win . . . how can we not cheer for David?
Author: David F. Treagust
Publisher: Springer
ISBN: 3319589148
Category : Science
Languages : en
Pages : 329
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Book Description
This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning is still a gap in physics education. The research presented in the three sections of the book is introduced by descriptions of various psychological theories that are applied in different ways for designing physics teaching and learning in classroom settings. The following chapters of the book illustrate teaching and learning with respect to applying specific physics multiple representations in different levels of the education system and in different physics topics using analogies and models, different modes, and in reasoning and representational competence. When multiple representations are used in physics for teaching, the expectation is that they should be successful. To ensure this is the case, the implementation of representations should consider design principles for using multiple representations. Investigations regarding their effect on classroom communication as well as on the learning results in all levels of schooling and for different topics of physics are reported. The book is intended for physics educators and their students at universities and for physics teachers in schools to apply multiple representations in physics in a productive way.
