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Data Structures using C A Practical Approach for Beginners

Data Structures using C A Practical Approach for Beginners

The data structure is a set of specially organized data elements and functions which are defined to store retrieve remove and search for individual data elements. Data Structures using C: A Practical Approach for Beginners covers all issues related to the amount of storage needed the amount of time required to process the data data representation of the primary memory and operations carried out with such data. Data Structures using C: A Practical Approach for Beginners book will help students learn data structure and algorithms in a focused way. Resolves linear and nonlinear data structures in C language using the algorithm diagrammatically and its time and space complexity analysis Covers interview questions and MCQs on all topics of campus readiness Identifies possible solutions to each problem Includes real-life and computational applications of linear and nonlinear data structures This book is primarily aimed at undergraduates and graduates of computer science and information technology. Students of all engineering disciplines will also find this book useful. | Data Structures using C A Practical Approach for Beginners

GBP 105.00
1

A Criminologist's Guide to R Crime by the Numbers

A Criminologist's Guide to R Crime by the Numbers

A Criminologist's Guide to R: Crime by the Numbers introduces the programming language R and covers the necessary skills to conduct quantitative research in criminology. By the end of this book a person without any prior programming experience can take raw crime data be able to clean it visualize the data present it using R Markdown and change it to a format ready for analysis. A Criminologist's Guide to R focuses on skills specifically for criminology such as spatial joins mapping and scraping data from PDFs however any social scientist looking for an introduction to R for data analysis will find this useful. Key Features: Introduction to RStudio including how to change user preference settings. Basic data exploration and cleaning – subsetting loading data regular expressions aggregating data. Graphing with ggplot2. How to make maps (hotspot maps choropleth maps interactive maps). Webscraping and PDF scraping. Project management – how to prepare for a project how to decide which projects to do best ways to collaborate with people how to store your code (using git) and how to test your code. | A Criminologist's Guide to R Crime by the Numbers

GBP 74.99
1

Population Genomics with R

Population Genomics with R

Population Genomics With R presents a multidisciplinary approach to the analysis of population genomics. The methods treated cover a large number of topics from traditional population genetics to large-scale genomics with high-throughput sequencing data. Several dozen R packages are examined and integrated to provide a coherent software environment with a wide range of computational statistical and graphical tools. Small examples are used to illustrate the basics and published data are used as case studies. Readers are expected to have a basic knowledge of biology genetics and statistical inference methods. Graduate students and post-doctorate researchers will find resources to analyze their population genetic and genomic data as well as help them design new studies. The first four chapters review the basics of population genomics data acquisition and the use of R to store and manipulate genomic data. Chapter 5 treats the exploration of genomic data an important issue when analysing large data sets. The other five chapters cover linkage disequilibrium population genomic structure geographical structure past demographic events and natural selection. These chapters include supervised and unsupervised methods admixture analysis an in-depth treatment of multivariate methods and advice on how to handle GIS data. The analysis of natural selection a traditional issue in evolutionary biology has known a revival with modern population genomic data. All chapters include exercises. Supplemental materials are available on-line (http://ape-package. ird. fr/PGR. html).

GBP 48.99
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Hands-On Data Science for Librarians

Hands-On Data Science for Librarians

Librarians understand the need to store use and analyze data related to their collection patrons and institution and there has been consistent interest over the last 10 years to improve data management analysis and visualization skills within the profession. However librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping working with maps creating interactive reports machine learning and others. While there’s a place for theory ethics and statistical methods librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work no matter what type of library they work at (academic public or special). By walking through each skill and its application to library work before walking the reader through each line of code this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public academic or special) as well as graduate students in library and information science (LIS). Key Features: Only data science book available geared toward librarians that includes step-by-step code examples Examples include all library types (public academic special) Relevant datasets Accessible to non-technical professionals Focused on job skills and their applications

GBP 52.99
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Medical Internet of Things Techniques Practices and Applications

Medical Internet of Things Techniques Practices and Applications

In recent years the Medical Internet of Things (MIoT) has emerged as one of the most helpful technological gifts to mankind. With the incredible development in data science big data technologies IoT and embedded systems it is now possible to collect a huge amount of sensitive and personal data compile it and store it through cloud or edge computing techniques. However important concerns remain about security and privacy the preservation of sensitive and personal data and the efficient transfer storage and processing of MIoT-based data. Medical Internet of Things: Techniques Practices and Applications is an attempt to explore new ideas and novel techniques in the area of MIoT. The book is composed of fifteen chapters discussing basic concepts issues challenges case studies and applications in MIoT. This book offers novel advances and applications of MIoT in a precise and clear manner to the research community to achieve in-depth knowledge in the field. This book will help those interested in the field as well as researchers to gain insight into different concepts and their importance in multifaceted applications of real life. This has been done to make the book more flexible and to stimulate further interest in the topic. Features: A systematic overview of concepts in Medical Internet of Things (MIoT) is included. Recent research and some pointers on future advancements in MIoT are discussed. Examples and case studies are included. It is written in an easy-to-understand style with the help of numerous figures and datasets. This book serves as a reference book for scientific investigators who are interested in working on MIoT as well as researchers developing methodology in this field. It may also be used as a textbook for postgraduate-level courses in computer science or information technology. | Medical Internet of Things Techniques Practices and Applications

GBP 130.00
1