This article on a complete tutorial to learn Data Science in R from scratch, was posted by Manish Saraswat. Manish who works in marketing and Data Science at Analytics Vidhya believes that education can change this world. R, Data Science and Machine Learning keep him busy.
R is a powerful language used widely for data analysis and statistical computing. It was developed in early 90s. Since then, endless efforts have been made to improve R’s user interface. The journey of R language from a rudimentary text editor to interactive R Studio and more recently Jupyter Notebooks has engaged many data science communities across the world.
What you can find in this article :
1 Basics of R Programming for Data Science
- Why learn R ?
- How to install R / R Studio ?
- How to install R packages ?
- Basic computations in R
2 Essentials of R Programming
- Data Types and Objects in R
- Control Structures (Functions) in R
- Useful R Packages
3 Exploratory Data Analysis in R
- Basic Graphs
- Treating Missing values
- Working with Continuous and Categorical Variables
4 Data Manipulation in R
- Feature Engineering
- Label Encoding / One Hot Encoding
5 Predictive Modeling using Machine Learning in R
- Linear Regression
- Decision Tree
- Random Forest
You can find the full article here. For other articles about R, click here.
DSC Resources
- Career: Training | Books | Cheat Sheet | Apprenticeship | Certification | Salary Surveys | Jobs
- Knowledge: Research | Competitions | Webinars | Our Book | Members Only | Search DSC
- Buzz: Business News | Announcements | Events | RSS Feeds
- Misc: Top Links | Code Snippets | External Resources | Best Blogs | Subscribe | For Bloggers
Additional Reading
- What statisticians think about data scientists
- Data Science Compared to 16 Analytic Disciplines
- 10 types of data scientists
- 91 job interview questions for data scientists
- 50 Questions to Test True Data Science Knowledge
- 24 Uses of Statistical Modeling
- 21 data science systems used by Amazon to operate its business
- Top 20 Big Data Experts to Follow (Includes Scoring Algorithm)
- 5 Data Science Leaders Share their Predictions for 2016 and Beyond
- 50 Articles about Hadoop and Related Topics
- 10 Modern Statistical Concepts Discovered by Data Scientists
- Top data science keywords on DSC
- 4 easy steps to becoming a data scientist
- 22 tips for better data science
- How to detect spurious correlations, and how to find the real ones
- 17 short tutorials all data scientists should read (and practice)
- High versus low-level data science
Follow us on Twitter: @DataScienceCtrl | @AnalyticBridge