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Learn all about R (programming language)

by Innoware Pjp
Save 12% Save 12%
Current price ₹2,166.00
Original price ₹2,450.00
Original price ₹2,450.00
Original price ₹2,450.00
(-12%)
₹2,166.00
Current price ₹2,166.00

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Book cover type: Paperback
  • ISBN13: 9798395275554
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 184
  • Original Price: USD 24.99
  • Language: English
  • Edition: N/A
  • Item Weight: 254 grams
  • BISAC Subject(s): Computers & Technology

Learn all about R (programming language for statistical computing and graphics)

The book covers the following topics:

1. Introduction to R
Brief history and development of R
Installing R and RStudio
Basic concepts and features of R

2. Getting Started with R
R syntax and basic operations
Variables, data types, and data structures in R
Working with vectors, matrices, and arrays
Introduction to data frames

3. Data Manipulation and Analysis
Importing and exporting data in R
Data cleaning and preprocessing
Exploratory data analysis
Data visualization using base R graphics and packages like ggplot2

4. Programming in R
Control structures (if-else, loops)
Functions and their usage
Error handling and debugging techniques
Writing efficient and readable code

5. Statistical Analysis with R
Descriptive statistics and summary measures
Hypothesis testing and statistical inference
Regression analysis (linear regression, logistic regression)
Time series analysis and forecasting
Multivariate analysis (clustering, factor analysis)

6. Advanced Topics in R
Object-oriented programming in R
Creating and using packages in R
Parallel computing and performance optimization
Web scraping and accessing APIs in R

7. R for Machine Learning
Introduction to machine learning concepts
Supervised learning (classification, regression)
Unsupervised learning (clustering, dimensionality reduction)
Model evaluation and selection

8. R for Big Data
Working with large datasets in R
Introduction to distributed computing frameworks (e.g., Spark)
Using R for big data analytics

9. R in Practice
Case studies and real-world examples
Best practices for R programming
Tips and tricks for efficient R usage

10. Resources and Next Steps
Additional learning resources (books, websites, online courses)
R community and support forums
Advanced topics and specialized packages
Future trends and developments in R

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