Learning R And Python For Business School Students
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Learning R And Python For Business School Students
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Author : Yuxing Yan
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2022-11-04
Learning R And Python For Business School Students written by Yuxing Yan and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-04 with Computers categories.
This book provides a guide for business school students, individual investors, and business professionals to learn R and Python, two open-source programming languages. It is unique since it allows the reader to learn programming in an “R-assisted learning environment”. The book provides 15 weeks’ worth of teaching material for the reader.
Python For Finance
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Author : Yves J. Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-12-05
Python For Finance written by Yves J. Hilpisch and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-05 with Computers categories.
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
An Introduction To Statistical Learning
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Author : Gareth James
language : en
Publisher: Springer Nature
Release Date : 2023-06-30
An Introduction To Statistical Learning written by Gareth James and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Mathematics categories.
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Learning Python
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Author : Mark Lutz
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-06-12
Learning Python written by Mark Lutz and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-12 with Computers categories.
Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code. Explore Python’s major built-in object types such as numbers, lists, and dictionaries Create and process objects with Python statements, and learn Python’s general syntax model Use functions to avoid code redundancy and package code for reuse Organize statements, functions, and other tools into larger components with modules Dive into classes: Python’s object-oriented programming tool for structuring code Write large programs with Python’s exception-handling model and development tools Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing
R For Data Science
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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-12
R For Data Science written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-12 with Computers categories.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Introduction To Fintech Using Excel
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Author : Yuxing Yan
language : en
Publisher: Springer Nature
Release Date : 2025-08-20
Introduction To Fintech Using Excel written by Yuxing Yan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-20 with Business & Economics categories.
This book serves as a bridge, leveraging the familiarity of Excel and the power of R to make FinTech accessible to all. Financial Technology (FinTech) has revolutionized areas once dominated by traditional finance. However, the need to learn a programming language often creates a barrier for many learners. Excel-based learning builds confidence with tools that are already familiar to advanced students, while minimal R programming is required—no prior R skills needed, just two simple lines of code. Hidden functions unlock powerful FinTech capabilities with ease. With this book, students can learn to generate public and private keys effortlessly,create a Hash for any given phrase, use the Merkle Tree to combine 100 transactions into a block's Hash, develop QR codes for websites or public keys, verify (x,y) values on the Elliptic curve for cryptography, and run models for both Unsupervised and Supervised Learning. The book includes definitions, exercises, and solutions for students to develop the skills to navigate and excel in the world of FinTech.
Behavioral Data Analysis With R And Python
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Author : Florent Buisson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-15
Behavioral Data Analysis With R And Python written by Florent Buisson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Business & Economics categories.
Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way
Comparative Approaches To Using R And Python For Statistical Data Analysis
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Author : Sarmento, Rui
language : en
Publisher: IGI Global
Release Date : 2017-01-06
Comparative Approaches To Using R And Python For Statistical Data Analysis written by Sarmento, Rui and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-06 with Business & Economics categories.
The application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users. Comparative Approaches to Using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis.
Python And R For The Modern Data Scientist
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Author : Rick J. Scavetta
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-22
Python And R For The Modern Data Scientist written by Rick J. Scavetta and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-22 with Computers categories.
Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together
Coding Literacy
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Author : Annette Vee
language : en
Publisher: MIT Press
Release Date : 2017-07-28
Coding Literacy written by Annette Vee and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.
How the theoretical tools of literacy help us understand programming in its historical, social and conceptual contexts. The message from educators, the tech community, and even politicians is clear: everyone should learn to code. To emphasize the universality and importance of computer programming, promoters of coding for everyone often invoke the concept of “literacy,” drawing parallels between reading and writing code and reading and writing text. In this book, Annette Vee examines the coding-as-literacy analogy and argues that it can be an apt rhetorical frame. The theoretical tools of literacy help us understand programming beyond a technical level, and in its historical, social, and conceptual contexts. Viewing programming from the perspective of literacy and literacy from the perspective of programming, she argues, shifts our understandings of both. Computer programming becomes part of an array of communication skills important in everyday life, and literacy, augmented by programming, becomes more capacious. Vee examines the ways that programming is linked with literacy in coding literacy campaigns, considering the ideologies that accompany this coupling, and she looks at how both writing and programming encode and distribute information. She explores historical parallels between writing and programming, using the evolution of mass textual literacy to shed light on the trajectory of code from military and government infrastructure to large-scale businesses to personal use. Writing and coding were institutionalized, domesticated, and then established as a basis for literacy. Just as societies demonstrated a “literate mentality” regardless of the literate status of individuals, Vee argues, a “computational mentality” is now emerging even though coding is still a specialized skill.