R Programming Bootcamp for Data Science and Machine Learning

About R Programming Bootcamp for Data Science and Machine Learning

Introduction

R Installation

Installing and Exploring RStudio

Why Learn R

First R Program and Operators in R

Data Types in R

Creating Vectors in R

Sequence in R

Replicate Function

Accessing Vector Elements

Vector Manipulation in R

Vector Elements Recycling

Sorting Vector Elements

Decision Making in R

Loop Control using repeat and while loop

For loop and next statement

Functions in R

Matrices in R

Factors in R

Data Frames in R

Combining Data Frames

Analysing Data in R from CSV file

Creating Pie chart in R

Analyzing Employee Data

Reading excel file in R

Reading xml file in R

Reading JSON file in R

Creating Bar plot

Stacked Bar Chart in R

Boxplot in R

Boxlot using mtcars dataset

Boxplot with notch

Histogram and distribution of Histogram

Drawing Histogram using hist function

Using breaks xlim ylim in histogram

Basic line chart for time series with ggplot2

Scatter Plot and plot matrices in R

Finding mean in R

Finding median and mode in R

What is Linear Regression

Prediction Using Linear Regression Model

Reading CSV creating LR model and Predicting

Multiple Regression

Predicting Car Mileage using Multiple Regression in R

Logistic Regression

Normal Distribution

Normal Distribution using dnorm and pnorm function

Normal Distribution using qnorm and rnorm function

Recursion in R

Finding Factorial of a number using recursion in R

Sample Data from a Population

Program to check Prime Numbers

Program to check EVEN or ODD

Program to check Positive Negative or ZERO

Program to Check Leap Year or NOT

Program for Multiplication Table

What are Missing Values and Types of Missing Values

Imputing Missing Values NAs in data set

Imputing Missing Values using PMM method

Analyzing Data sets using R functions

Data Manipulation Using dplyr package

Introduction to Shiny Interactive Dashboards in R

ShinyApp Creating Interactive Dashboard with Shiny

Some Examples of Shiny Apps in R

2 File Shiny App in RStudio

Generating Downloadable Reports in Shiny

Analysis of Covariance

Handson with dplyr library

Simple Linear Regression Using Airquality dataset

Dealing With Missing Values

Test the Missing Values

Recode the Missing Values

Decision Tree

Entropy And Information Gain

Calculating Entropy in Decision Tree

Calculating Information Gain for Decision Tree

Hands on Decision Tree in R

Advantages and Disadvantages of Decision Tree

Project 1 Introduction

Project 1 - Predicting Stock Prices

Project 2 Uber Data Analysis using R

Project 3 Customer Segmentation using R

Project 3 Part 2 Customer Segmentation using R

Project 4 - Introduction - Movies Recommendation

Project 4 -Part 1- Movie Recommendation System using R

Project 4- Part 2- Movie Recommender System

Project 5 Introduction Credit Card Fraud Detection

Importance of Online Fraud Detection

Dealing with Imbalanced Dataset

Fraud Detection with No Model

Creating Training and Test Datasets Sampling

Random Sampling Methods Over and Under Sampling

Using ROS and RUS together for Data Balancing

Advantages and Disadvantages of SMOTE

Applying SMOTE Technique on the Training Dataset

Predicting Credit Card Transactions Cases with the Model

Introduction to ggplot2

Scatter plot and jittered plot

Bar Plot and Hostogram

Pie Chart with ggplot2

Line Plots using ggplot2

Data Visualization with ggplot2

Add color aesthetics to the plots

Fine tuning plot aesthetics

Modifying themes, labels, titles, and axes using theme Function

Project 6

Handling date and time data in ggplot2

POSIXct and POSIXlt functions with example

Project 7 Data transformation and Summarization

Project 7 Part 2 Data Filtering and Color Scales

Creating interactive plots with plotly and ggplotly

Introduction to Plotly and Key Features

Working with Plotly

Creating 3D Plots in R

Creating Interactive Plots with Highcharts

Project 8 Visualizing Airbnb Data in New York City

Project 9 COVID 19 Data Analysis and Visualization

Project 10 Drawing Flowers using Mathematics in R

Project 11 Analysing and Visualizing the Nobel Prize Winners using R

Project 12 Finding Password Strength using R

Introduction to Machine Learning

The Role of Machine Learning

Machine Learning Types

Machine Learning Workflow

GIGO Principle

Supervised Learning Algorithms

Linear Regression

Performing Linear Regression in R

Predict the height of a person using linear regression

Logistic Regression

Customer Churn Prediction using Logistic Regression

KNN algorithm

Implementing kNN

Decision Tree and Random Forests

Support Vector Machines Algorithm

Understanding Regression Analysis

Understanding Linear Regression Model

Understanding Homescedasticity

Understanding Normality

Understanding No Perfect Multicollinearity

Simple Linear Regression Concepts and Formulation

The Least Squares Method Theory Explained

Example Least Square Method in Linear Regression

Conclusion and Project Work