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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: Osvaldo Gervasi
Publisher: Springer Nature
ISBN: 3030869709
Category : Computers
Languages : en
Pages : 749
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Book Description
The ten-volume set LNCS 12949 – 12958 constitutes the proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, which was held in Cagliari, Italy, during September 13 – 16, 2021. The event was organized in a hybrid mode due to the Covid-19 pandemic.The 466 full and 18 short papers presented in these proceedings were carefully reviewed and selected from 1588 submissions. The books cover such topics as multicore architectures, mobile and wireless security, sensor networks, open source software, collaborative and social computing systems and tools, cryptography, human computer interaction, software design engineering, and others. Part III of the set icludes papers on Information Systems and Technologies and the proceeding of the following workshops: International Workshop on Automatic landform classification: spatial methods and applications (ALCSMA 2021); International Workshop on Application of Numerical Analysis to Imaging Science (ANAIS 2021); International Workshop on Advances in information Systems and Technologies for Emergency management, risk assessment and mitigationbased on the Resilience concepts (ASTER 2021); International Workshop on Advances in Web Based Learning (AWBL 2021).
Author:
Publisher: Independently Published
ISBN:
Category :
Languages : es
Pages : 264
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Book Description
Python para Todos está diseñado para introducir a los estudiantes en la programación y el desarrollo de software a través de un enfoque en la exploración de datos. Puedes pensar en Python como una herramienta para resolver problemas que están más allá de las capacidades de una simple hoja de cálculo.Python es un lenguaje de programación fácil de usar y sencillo de aprender, disponible de forma gratuita para equipos Macintosh, Windows, o Linux. Una vez que aprendes Python, puedes utilizarlo el resto de tu carrera sin necesidad de comprar ningún software.Existen copias electrónicas gratuitas de este libro en varios formatos, así como material de soporte para el libro, que pues encontrar en es.py4e.com. Los materiales del curso están disponibles bajo una Licencia Creative Commons, de modo que puedes adaptarlos para enseñar tu propio curso de Python.
Author: Joseph Schmuller
Publisher: John Wiley & Sons
ISBN: 1119337062
Category : Computers
Languages : en
Pages : 467
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Book Description
Understanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data—the fast and easy way!
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: 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: 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: National Research Council
Publisher: National Academies Press
ISBN: 0309297990
Category : Education
Languages : en
Pages : 143
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Book Description
STEM Integration in K-12 Education examines current efforts to connect the STEM disciplines in K-12 education. This report identifies and characterizes existing approaches to integrated STEM education, both in formal and after- and out-of-school settings. The report reviews the evidence for the impact of integrated approaches on various student outcomes, and it proposes a set of priority research questions to advance the understanding of integrated STEM education. STEM Integration in K-12 Education proposes a framework to provide a common perspective and vocabulary for researchers, practitioners, and others to identify, discuss, and investigate specific integrated STEM initiatives within the K-12 education system of the United States. STEM Integration in K-12 Education makes recommendations for designers of integrated STEM experiences, assessment developers, and researchers to design and document effective integrated STEM education. This report will help to further their work and improve the chances that some forms of integrated STEM education will make a positive difference in student learning and interest and other valued outcomes.
