Data Science With R An Integrated Approach To Programming And Analytics
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Data Science With R An Integrated Approach To Programming And Analytics
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Author : Prof.Lavanya.V
language : en
Publisher: Leilani Katie Publication
Release Date : 2025-05-07
Data Science With R An Integrated Approach To Programming And Analytics written by Prof.Lavanya.V and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
Prof.Lavanya.V, Assistant Professor, Department of Computer Applications, CMR University, Bengaluru, Karnataka, India. Prof.N.Bhavyadevi Vishalakshi, Assistant Professor, Department of Computer Science and Engineering, CMR University, Bengaluru, Karnataka, India. Dr.T.Priya, Assistant Professor, Department of Computer Applications, East Point College of Higher Education, Bengaluru, Karnataka, India. Dr.S.Moses Praveen Mukharjee, Professor, Department of Computer Applications, East Point College of Higher Education, Bengaluru, Karnataka, India.
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
Data Science With R Programming
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Author : Dr.CARMEL MARY BELINDA.M.J
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-02-07
Data Science With R Programming written by Dr.CARMEL MARY BELINDA.M.J and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-07 with Computers categories.
Dr.CARMEL MARY BELINDA.M.J, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.K.NATTAR KANNAN, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.R.GNANAJEYARAMAN, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical And Technical Sciences, Saveetha University, Chennai, India. Dr.U.ARUL, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.M.RAMA MOORTHY, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.
Real Time Data Analytics And R Programming
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Author : Dr.J.Chenni Kumaran
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-02-05
Real Time Data Analytics And R Programming written by Dr.J.Chenni Kumaran and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-05 with Language Arts & Disciplines categories.
Dr.J.Chenni Kumaran, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.M.Sivaram, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.A.Manimaran, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.A.Selvakumar, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.S. Ramesh, Profesor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.
R Programming
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Author : Dr.R.GOPINATH
language : en
Publisher: SK Research Group of Companies
Release Date : 2023-10-23
R Programming written by Dr.R.GOPINATH and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-23 with Computers categories.
Dr.R.GOPINATH, Associate Professor, Department of Computer Science and Engineering, K.S.Rangasamy College of Technology (Autonomous), Tiruchengode, Tamil Nadu, India. Dr.A.GNANABASKARAN, Professor, Department of Computer Science and Engineering, K.S.Rangasamy College of Technology (Autonomous), Tiruchengode, Tamil Nadu, India. Mr.P.SATHISHKUMAR, Associate Professor, Department of Computer Science and Engineering, K.S.Rangasamy College of Technology (Autonomous), Tiruchengode, Tamil Nadu, India. Mr.R.VIJAY SAI, Assistant Professor, Department of Computer Science and Engineering, K.S.Rangasamy College of Technology (Autonomous), Tiruchengode, Tamil Nadu, India.
Beginning Data Science In R
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Author : Thomas Mailund
language : en
Publisher: Apress
Release Date : 2017-03-09
Beginning Data Science In R written by Thomas Mailund and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-09 with Computers categories.
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.
Data Science Fundamentals And Practical Approaches
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Author : Nandi Dr. Rupam Dr. Gypsy, Kumar Sharma
language : en
Publisher: BPB Publications
Release Date : 2020-09-03
Data Science Fundamentals And Practical Approaches written by Nandi Dr. Rupam Dr. Gypsy, Kumar Sharma and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-03 with Language Arts & Disciplines categories.
Learn how to process and analysis data using Python Key Features a- The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. a- The book is quite well balanced with programs and illustrative real-case problems. a- The book not only deals with the background mathematics alone or only the programs but also beautifully correlates the background mathematics to the theory and then finally translating it into the programs. a- A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-answer questions. Description This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems. Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic. What will you learn a- Understand what machine learning is and how learning can be incorporated into a program. a- Perform data processing to make it ready for visual plot to understand the pattern in data over time. a- Know how tools can be used to perform analysis on big data using python a- Perform social media analytics, business analytics, and data analytics on any data of a company or organization. Who this book is for The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. The book can be read by anyone who has an interest in data analysis and would like to explore more out of interest or to apply it to certain real-life problems. Table of Contents 1. Fundamentals of Data Science1 2. Data Preprocessing 3. Data Plotting and Visualization 4. Statistical Data Analysis 5. Machine Learning for Data Science 6. Time-Series Analysis 7. Deep Learning for Data Science 8. Social Media Analytics 9. Business Analytics 10. Big Data Analytics About the Authors Dr. Gypsy Nandi is an Assistant Professor (Sr) in the Department of Computer Applications, Assam Don Bosco University, India. Her areas of interest include Data Science, Social Network Mining, and Machine Learning. She has completed her Ph.D. in the field of 'Social Network Analysis and Mining'. Her research scholars are currently working mainly in the field of Data Science. She has several research publications in reputed journals and book series. Dr. Rupam Kumar Sharma is an Assistant Professor in the Department of Computer Applications, Assam Don Bosco University, India. His area of interest includes Machine Learning, Data Analytics, Network, and Cyber Security. He has several research publications in reputed SCI and Scopus journals. He has also delivered lectures and trained hundreds of trainees and students across different institutes in the field of security and android app development.
Data Science Ai And Blockchain
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Author : Ekaaksh Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Data Science Ai And Blockchain written by Ekaaksh Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
"Data Science, AI, and Blockchain: Integrated Approaches" emerges as a beacon for undergraduate students navigating the intricate landscapes of these transformative technologies. Our primary objective is to empower students with a comprehensive understanding of the synergy between Data Science, Artificial Intelligence (AI), and Blockchain, recognizing them as pivotal forces propelling innovation across diverse industries. We begin with Data Science, centered on extracting knowledge and insights from vast datasets, navigating through fundamental principles, methodologies, and tools. Real-world applications illustrate the significance of data-driven decision-making. Seamlessly moving into Artificial Intelligence, the book demystifies the algorithms underpinning intelligent systems. By weaving together theoretical concepts with practical examples, students gain insights into machine learning, natural language processing, and computer vision. Ethical considerations accompany the exploration, urging students to contemplate societal impacts. The exploration culminates in Blockchain, a revolutionary technology disrupting traditional notions of trust and transparency. Students understand how Blockchain secures transactions, empowers smart contracts, and transforms industries. Practical insights into building decentralized applications (DApps) are provided. Interactive elements, case studies, and exercises engage students actively. By fostering a multidisciplinary approach, we aim to equip undergraduates with the knowledge and skills needed to thrive in a world where the convergence of Data Science, AI, and Blockchain is reshaping the future.
Data Science And Analytics
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Author : Usha Batra
language : en
Publisher: Springer Nature
Release Date : 2020-05-27
Data Science And Analytics written by Usha Batra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-27 with Computers categories.
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.
Programming Skills For Data Science
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Author : Freeman
language : en
Publisher: Pearson Education India
Release Date :
Programming Skills For Data Science written by Freeman and has been published by Pearson Education India this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Programming Skills for Data Science brings together all the foundation skills needed to transform raw data into actionable insights for domains ranging from urban planning to precision medicine, even if you have no programming or data science experience. Guided by expert instructors Michael Freeman and Joel Ross, this book will help learners install the tools required to solve professional-level data science problems, including widely used R language, RStudio integrated development environment, and Git version-control system. It explains how to wrangle data into a form where it can be easily used, analyzed, and visualized so others can see the patterns uncovered. Step by step, students will master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.