gagan-gv / R-Notes-For-DS-ML

R-Notes

R Notes For DS and ML

What is Data Science(DS)?

Data Science is the art of discovering insights, trends and patterns from raw data.

What is Machine Learning(ML)?

According to wikipedia, it's an study of algorithms that improve through experience.

Basic points

• <- or = can be used as assignment operator
• '#' (without quotes) is used for comments
• to check a documentation of any predefined function one can use ? before the function name for e.g., ?mean() or dataset or packages
• To check long-form documentation use vignette()
• R doesn't follow similar index conventions of other languages as the index value starts from 1 in R not 0 thus making it more real world application.
• R commonly uses . notation for naming functions but tidyverse package uses _ notation for naming functions

Index to follow

1. Data Types
   1. Basic Data Types
   2. Vectors
   3. Matrices
   4. Lists
   5. Data Frames
   6. Tibbles
2. Intermediate R
   1. Overview
   2. Relational Operators
   3. Logical Operators
   4. Conditional Statements
   5. Loops
   6. Functions
   7. Packages
   8. Factors
   9. Dates and Times
   10. Functional Programming
   11. Data Import and Export
   12. Working with Databases in R
3. Data Manipulation
   1. Overview
   2. Tidy Data
   3. Pipe Operator
   4. Verbs
   5. Data Pivoting
   6. String Manipulation
   7. Web Scraping
4. Data Visualization
   1. Overview
   2. Basics of ggplot2
   3. Aesthetics Mapping
   4. Single Variable Plot
   5. Double Variable Plot
   6. Facets, Layers and Coordinate System
   7. Styling
   8. Text Visualization (Word Cloud)
5. Data Preprocessing
   1. Overview
   2. Code
6. Exploratory Data Analysis
   1. Overview
   2. Code
7. Model Devlopment
   1. Steps

Resources:

• https://tidyverse.org
• https://r4ds.had.co.nz
• https://tidymodels.org