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Data Science Essentials with R | data manipulation, visualization, and machine learning |Abhishek Das | New Editions | BPB Publications (English Medium)
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| 679-837 |
Data Science Essentials with R | data manipulation, visualization, and machine learning |Abhishek Das | New Editions | BPB Publications (English Medium)
Data Science Essentials with R is a comprehensive guide that covers all the essential aspects of data science using the R programming language. Authored by Abhishek Das, this new edition from BPB Publications is designed to help readers learn the fundamentals of data manipulation, visualization, and machine learning using R.
The book starts with an introduction to data science and its importance in today's digital world. It then dives into the basics of R programming, covering topics such as data types, variables, functions, and loops. Readers will also learn how to import and export data in R, perform basic data manipulation tasks like sorting and filtering, and create visualizations using popular packages like ggplot2.
As readers progress through the book, they will explore more advanced topics such as statistical analysis, machine learning algorithms, and predictive modeling. The author provides step-by-step instructions on how to build various machine learning models in R, including linear regression, logistic regression, decision trees, random forests, and support vector machines.
In addition to theoretical concepts, Data Science Essentials with R also includes practical examples and hands-on exercises to help readers apply their knowledge in real-world scenarios. The book comes with downloadable datasets and code snippets that can be used to practice different techniques discussed in each chapter.
Whether you are a beginner looking to get started in data science or an experienced professional seeking to enhance your skills with R programming, this book is a valuable resource for anyone interested in mastering the essentials of data manipulation, visualization, and machine learning.
With its clear explanations, detailed examples, and practical exercises, Data Science Essentials with R is a must-have guide for anyone looking to excel in the field of data science using the powerful capabilities of the R programming language.
Publisher : BPB Publications, Publication date : 30 December 2024, Language : English, Print length : 268 pages, ISBN-10 : 9365895294, ISBN-13 : 978-9365895292, Item Weight : 467 g, Dimensions : 19.05 x 1.55 x 23.5 cm, Country of Origin : India
Data Science Essentials with R by Abhishek Das is a comprehensive and practical guide designed to introduce readers to the core concepts of data science using the powerful R programming language. With the growing importance of data-driven decision-making across industries, this book provides a structured pathway for learners to build strong analytical and technical skills required in today’s data-centric world.
The book begins with the fundamentals of R programming, making it accessible to beginners with little or no prior coding experience. It introduces key concepts such as data types, variables, and control structures, helping readers establish a solid foundation. As the book progresses, it gradually moves into more advanced topics, ensuring a smooth and logical learning curve.
A major focus of the book is on data manipulation and cleaning, which are critical steps in any data science workflow. Readers will learn how to handle raw data, transform it into meaningful formats, and prepare it for analysis using powerful R libraries such as dplyr. These practical techniques enable users to work efficiently with real-world datasets.
Data visualization is another key area covered in the book. It teaches readers how to create insightful and visually appealing charts and graphs that help communicate data effectively. By understanding how to visualize data, readers can uncover patterns, trends, and insights that are essential for informed decision-making.
The book also introduces essential statistical concepts, including probability, hypothesis testing, and statistical modeling. These topics provide the theoretical foundation required to analyze data and draw meaningful conclusions. The explanations are clear and supported by examples, making complex ideas easier to understand.
Moving beyond fundamentals, the book explores machine learning techniques, covering both supervised and unsupervised learning methods. Readers will learn about classification, regression, clustering, and feature engineering, along with model evaluation techniques. These skills are crucial for building predictive models and solving real-world problems.
In addition to technical knowledge, the book provides valuable guidance for building a career in data science. It offers insights into the skills required, industry trends, and strategies for job searching and professional growth. This makes the book not only a learning resource but also a career development guide.
With its practical approach, real-world examples, and step-by-step explanations, this book is ideal for students, aspiring data scientists, analysts, and professionals looking to upskill. It bridges the gap between theory and practice, enabling readers to apply their knowledge effectively in real scenarios.
By the end of this book, you will have a strong understanding of data science concepts and the ability to work confidently with data using R. Data Science Essentials with R equips you with the tools and skills needed to analyze data, build models, and make data-driven decisions in a competitive and rapidly evolving field.
Search Keywords - Data Science Essentials with R book, Abhishek Das Data Science Essentials, Data manipulation techniques in R, Visualization tools in R, Machine learning algorithms with R, Best books on data science, BPB Publications new editions, How to learn data science with R, Step-by-step guide to data science, Practical exercises for data scientists, Downloadable datasets for machine learning, Mastering predictive modeling with R, Beginner's guide to data science, Advanced topics in data manipulation, Visualizing big data with ggplot2, Building machine learning models in R, Linear regression tutorial with R, Logistic regression examples in R, Decision tree implementation in R, Support vector machines explained 1. Data Science Essentials with R book, 2. Abhishek Das data science book, 3. Data manipulation techniques in R, 4. Data visualization in R, 5. Machine learning with R, 6. Best books on data science, 7. BPB Publications data science books, 8. New editions of data science books, 9. English medium data science books, 10. Top rated data science books ,
| SKU / BOOK Code: | DS-R-ESS-AD-2024 |
| Publisher: | BPB Publications |
| Author: | Abhishek Das (Author) |
| Binding Type: | Paperback |
| No. of Pages: | 268 |
| ISBN-10: | 9365895294 |
| ISBN-13: | 978-9365895292 |
| Edition: | New Editions |
| Language: | English Medium |
| Publish Year: | 2024-12 |
| Weight (g): | 467 |
| Product Condition: | New |
| Reading Age: | Above 18 Years |
| Country of Origin: | India |
| Genre: | Computers & Internet |
| Manufacturer: | BPB Publications |
| Importer: | BPB Publications |
| Packer: | Fullfilled by Supplier |
Data Science Essentials with R | data manipulation, visualization, and machine learning |Abhishek Das | New Editions | BPB Publications (English Medium)
Data Science Essentials with R is a comprehensive guide that covers all the essential aspects of data science using the R programming language. Authored by Abhishek Das, this new edition from BPB Publications is designed to help readers learn the fundamentals of data manipulation, visualization, and machine learning using R.
The book starts with an introduction to data science and its importance in today's digital world. It then dives into the basics of R programming, covering topics such as data types, variables, functions, and loops. Readers will also learn how to import and export data in R, perform basic data manipulation tasks like sorting and filtering, and create visualizations using popular packages like ggplot2.
As readers progress through the book, they will explore more advanced topics such as statistical analysis, machine learning algorithms, and predictive modeling. The author provides step-by-step instructions on how to build various machine learning models in R, including linear regression, logistic regression, decision trees, random forests, and support vector machines.
In addition to theoretical concepts, Data Science Essentials with R also includes practical examples and hands-on exercises to help readers apply their knowledge in real-world scenarios. The book comes with downloadable datasets and code snippets that can be used to practice different techniques discussed in each chapter.
Whether you are a beginner looking to get started in data science or an experienced professional seeking to enhance your skills with R programming, this book is a valuable resource for anyone interested in mastering the essentials of data manipulation, visualization, and machine learning.
With its clear explanations, detailed examples, and practical exercises, Data Science Essentials with R is a must-have guide for anyone looking to excel in the field of data science using the powerful capabilities of the R programming language.
Publisher : BPB Publications, Publication date : 30 December 2024, Language : English, Print length : 268 pages, ISBN-10 : 9365895294, ISBN-13 : 978-9365895292, Item Weight : 467 g, Dimensions : 19.05 x 1.55 x 23.5 cm, Country of Origin : India
Data Science Essentials with R by Abhishek Das is a comprehensive and practical guide designed to introduce readers to the core concepts of data science using the powerful R programming language. With the growing importance of data-driven decision-making across industries, this book provides a structured pathway for learners to build strong analytical and technical skills required in today’s data-centric world.
The book begins with the fundamentals of R programming, making it accessible to beginners with little or no prior coding experience. It introduces key concepts such as data types, variables, and control structures, helping readers establish a solid foundation. As the book progresses, it gradually moves into more advanced topics, ensuring a smooth and logical learning curve.
A major focus of the book is on data manipulation and cleaning, which are critical steps in any data science workflow. Readers will learn how to handle raw data, transform it into meaningful formats, and prepare it for analysis using powerful R libraries such as dplyr. These practical techniques enable users to work efficiently with real-world datasets.
Data visualization is another key area covered in the book. It teaches readers how to create insightful and visually appealing charts and graphs that help communicate data effectively. By understanding how to visualize data, readers can uncover patterns, trends, and insights that are essential for informed decision-making.
The book also introduces essential statistical concepts, including probability, hypothesis testing, and statistical modeling. These topics provide the theoretical foundation required to analyze data and draw meaningful conclusions. The explanations are clear and supported by examples, making complex ideas easier to understand.
Moving beyond fundamentals, the book explores machine learning techniques, covering both supervised and unsupervised learning methods. Readers will learn about classification, regression, clustering, and feature engineering, along with model evaluation techniques. These skills are crucial for building predictive models and solving real-world problems.
In addition to technical knowledge, the book provides valuable guidance for building a career in data science. It offers insights into the skills required, industry trends, and strategies for job searching and professional growth. This makes the book not only a learning resource but also a career development guide.
With its practical approach, real-world examples, and step-by-step explanations, this book is ideal for students, aspiring data scientists, analysts, and professionals looking to upskill. It bridges the gap between theory and practice, enabling readers to apply their knowledge effectively in real scenarios.
By the end of this book, you will have a strong understanding of data science concepts and the ability to work confidently with data using R. Data Science Essentials with R equips you with the tools and skills needed to analyze data, build models, and make data-driven decisions in a competitive and rapidly evolving field.
Search Keywords - Data Science Essentials with R book, Abhishek Das Data Science Essentials, Data manipulation techniques in R, Visualization tools in R, Machine learning algorithms with R, Best books on data science, BPB Publications new editions, How to learn data science with R, Step-by-step guide to data science, Practical exercises for data scientists, Downloadable datasets for machine learning, Mastering predictive modeling with R, Beginner's guide to data science, Advanced topics in data manipulation, Visualizing big data with ggplot2, Building machine learning models in R, Linear regression tutorial with R, Logistic regression examples in R, Decision tree implementation in R, Support vector machines explained 1. Data Science Essentials with R book, 2. Abhishek Das data science book, 3. Data manipulation techniques in R, 4. Data visualization in R, 5. Machine learning with R, 6. Best books on data science, 7. BPB Publications data science books, 8. New editions of data science books, 9. English medium data science books, 10. Top rated data science books ,
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