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Introduction to R for Quantitative Finance
This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.
Mastering R for Quantitative Finance
This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.
Mastering Data Analysis with R
Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful database...
R: Data Analysis and Visualization
Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analyt...
Data Analysis for Business, Economics, and Policy
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017)
This book is a product of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017) to be held in Langkawi in November 2017. It is divided into four sections according to the thrust areas: Computer Science, Mathematics, Statistics, and Multidisciplinary Applications. All sections sought to confront current issues that society faces today. The book brings collectively quantitative, as well as qualitative, research methods that are also suitable for future research undertakings. Researchers in Computer Science, Mathematics and Statistics can use this book as a sourcebook to enrich their research works.
Mastering Java for Data Science
Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you...
Java: Data Science Made Easy
Data collection, processing, analysis, and more About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples A highly practical course covering a broad set of topics - from the basics of Machine Learning to Deep Learning and Big Data frameworks. Who This Book Is For This course is meant for Java developers who are comfortable developing applications in Java, and now want to enter the world of data science or wish to build intelligent applications. Aspiring data scientists with some understanding of the Java programming language will also find this book to be very helpful...
R - FOR BASIC AND APPLIED SCIENCES
R is a Statistcal programming language. R is Free and open source. R is an interpreted language not a compiled one. The R programming environment contains the range of tools for parallel computing, machine and deep learning and for working with big Data, including Torch and Tensar flow facilitating construction and implementation of neural networks. The Bioconductor repository contains over a thousand of software packages written in R for analyzing data sets from CDNA microarrays to copy-number variation and epigenomics (Robert Gentleman-Sorin Draghicia). Due to Data Handling and Modeling capabilities and its flexibility, R is becoming the most widely used software in bioinformatics. The R p...
R语言计量金融初学指南
量化金融R语言初级教程,写给想要使用R语言完成量化金融任务的读者。学习量化金融领域强有力的工具,用R语言解决多种多样的问题 Key Features 通过实例讲解如何使用R解决各种定量问题 涵盖投资组合优化、资产定价模型、固定收益证券、估计利率期限结构、衍生品定价、信用风险管理、极值理论和金融网络等现实金融问题 Book DescriptionR是用于统计分析、绘图的语言和操作环境。它是属于GNU系统的一个自由、免费、源代码开放的软件,是一个用于统计计算和统计制图的优秀工具。 本书通过9章的内容向读者详细介绍使用R语言实现...
