Machine Learning Basics with R Studio
by
Start-Tech Academy
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Data Preprocessing
Data Preprocessing
Gathering Business Knowledge
4 mins
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Data Exploration
4 mins
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The Dataset and the Data Dictionary
8 mins
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Importing the dataset into R
3 mins
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Univariate analysis and EDD
4 mins
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EDD in R
13 mins
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Outlier Treatment
5 mins
Preview
Outlier Treatment in R
5 mins
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Missing Value Imputation
4 mins
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Missing Value imputation in R
4 mins
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Seasonality in Data
4 mins
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Bi-variate analysis and Variable transformation
17 mins
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Variable transformation in R
10 mins
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Non-usable variables
5 mins
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Dummy variable creation: Handling qualitative data
5 mins
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Dummy variable creation in R
6 mins
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Correlation Analysis
11 mins
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Correlation Matrix in R
9 mins
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Table of contents
Machine Learning Basics with R Studio
by
Start-Tech Academy
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Introduction
Introduction
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Welcome to the course!
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Welcome to the course!
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Course contents
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Course contents
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Course Resourses
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Course Resourses
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Basics of Statistics
Basics of Statistics
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Types of Statistics
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Types of Statistics
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Describing data Graphically
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Describing data Graphically
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Types of Data
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Types of Data
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Measures of Centers
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Measures of Centers
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Measures of Dispersion
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Measures of Dispersion
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Getting started with R and R studio
Getting started with R and R studio
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Installing R and R studio
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Installing R and R studio
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Basics of R and R studio
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Basics of R and R studio
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Packages in R
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Packages in R
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Inputting data part 1 - Inbuilt datasets of R
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Inputting data part 1 - Inbuilt datasets of R
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Inputting data part 2 - Manual data entry
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Inputting data part 2 - Manual data entry
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Inputting data part 3 - Importing from CSV or Text files
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Inputting data part 3 - Importing from CSV or Text files
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Creating Barplots in R
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Creating Barplots in R
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Creating Histograms in R
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Creating Histograms in R
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Introduction to Machine Learning
Introduction to Machine Learning
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Building a Machine Learning Model
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Building a Machine Learning Model
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Introduction to Machine Learning
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Introduction to Machine Learning
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Data Preprocessing
Data Preprocessing
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Gathering Business Knowledge
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Gathering Business Knowledge
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Data Exploration
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Data Exploration
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The Dataset and the Data Dictionary
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The Dataset and the Data Dictionary
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Importing the dataset into R
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Importing the dataset into R
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Univariate analysis and EDD
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Univariate analysis and EDD
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EDD in R
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EDD in R
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Outlier Treatment
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Outlier Treatment
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Outlier Treatment in R
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Outlier Treatment in R
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Missing Value Imputation
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Missing Value Imputation
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Missing Value imputation in R
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Missing Value imputation in R
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Seasonality in Data
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Seasonality in Data
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Bi-variate analysis and Variable transformation
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Bi-variate analysis and Variable transformation
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Variable transformation in R
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Variable transformation in R
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Non-usable variables
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Non-usable variables
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Dummy variable creation: Handling qualitative data
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Dummy variable creation: Handling qualitative data
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Dummy variable creation in R
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Dummy variable creation in R
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Correlation Analysis
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Correlation Analysis
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Correlation Matrix in R
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Correlation Matrix in R
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Linear Regression
Linear Regression
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Basic Equations and Ordinary Least Squares (OLS) method
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Basic Equations and Ordinary Least Squares (OLS) method
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The Problem Statement
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The Problem Statement
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Assessing accuracy of predicted coefficients
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Assessing accuracy of predicted coefficients
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Assessing Model Accuracy: RSE and R squared
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Assessing Model Accuracy: RSE and R squared
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Simple Linear Regression in R
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Simple Linear Regression in R
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Multiple Linear Regression
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Multiple Linear Regression
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The F - statistic
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The F - statistic
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Interpreting results of Categorical variables
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Interpreting results of Categorical variables
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Multiple Linear Regression in R
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Multiple Linear Regression in R
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Test-train split
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Test-train split
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Bias Variance trade-off
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Bias Variance trade-off
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Test-Train Split in R
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Test-Train Split in R
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Other Linear Models
Other Linear Models
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Linear models other than OLS
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Linear models other than OLS
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Subset selection techniques
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Subset selection techniques
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Subset Selection in R
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Subset Selection in R
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Shrinkage methods: Ridge and Lasso
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Shrinkage methods: Ridge and Lasso
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Ridge and Lasso in R
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Ridge and Lasso in R
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Extras: Heteroscedasticity
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Extras: Heteroscedasticity
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