## Introduction to Machine Learning in R

The word Machine Learning was first coined by Arthur Samuel in 1959. The definition of machine learning can be defined as that machine learning gives… Read More »

- Logistic Regression in R Programming
- Cross-Validation in R programming
- Random Forest Approach in R Programming
- XGBoost in R Programming
- Spearman Correlation Testing in R Programming
- Bootstrap Confidence Interval with R Programming
- Decision Tree for Regression in R Programming
- Random Forest Approach for Classification in R Programming
- How Neural Networks are used for Classification in R Programming
- Multi Layered Neural Networks in R Programming
- Predictive Analysis in R Programming
- Decision Tree Classifiers in R Programming
- Exploratory Data Analysis in R Programming
- Hierarchical Clustering in R Programming
- Single Layered Neural Networks in R Programming
- Kendall Correlation Testing in R Programming
- Lasso Regression in R Programming
- Association Rule Mining in R Programming
- Regression and its Types in R Programming
- R - Stem and Leaf Plots
- Time Series Analysis using ARIMA model in R Programming
- Ridge Regression in R Programming
- K-Means Clustering in R Programming
- Regression using k-Nearest Neighbors in R Programming
- Regression Analysis in R Programming
- Root-Mean-Square Error in R Programming
- Time Series Analysis using Facebook Prophet in R Programming
- Kolmogorov-Smirnov Test in R Programming
- Fisher’s F-Test in R Programming
- Random Forest Approach for Regression in R Programming

The word Machine Learning was first coined by Arthur Samuel in 1959. The definition of machine learning can be defined as that machine learning gives… Read More »

The major challenge in designing a machine learning model is to make it work accurately on the unseen data. To know whether the designed model… Read More »

Decision tree is a type of algorithm in machine learning that uses decisions as the features to represent the result in the form of a… Read More »

Machine learning is a subset of Artificial Intelligence that provides a machine with the ability to learn automatically without being explicitly programmed. The machine in… Read More »

Bootstrapping is a statistical method for inference about a population using sample data. It can be used to estimate the confidence interval(CI) by drawing samples… Read More »

Elastic Net regression is a classification algorithm that overcomes the limitations of the lasso(least absolute shrinkage and selection operator) method which uses a penalty function… Read More »

Ridge regression is a classification algorithm that works in part as it doesn’t require unbiased estimators. Ridge regression minimizes the residual sum of squares of… Read More »

Lasso regression is a classification algorithm that uses shrinkage in simple and sparse models(i.e model with fewer parameters). In Shrinkage, data values are shrunk towards… Read More »

Time Series Analysis is a way of analysing and learning the behaviour of datasets over a period. Moreover, it helps in learning the behavior of… Read More »

Machine Learning is a subset of Artificial Intelligence (AI), which is used to create intelligent systems that are able to learn without being programmed explicitly.… Read More »

Fisher’s F test calculates the ratio between the larger variance and the smaller variance. We use the F test when we want to check where… Read More »

Correlation is a statistical measure that indicates how strongly two variables are related. It involves the relationship between multiple variables as well. For instance, if… Read More »

The Kolmogorov-Smirnov Test is a type of non-parametric test of the equality of discontinuous and continuous of a 1D probability distribution that is used to… Read More »

The Exponential Smoothing is a technique for smoothing data of time series using an exponential window function. It is a rule of the thumb method.… Read More »

The concept used to generalize the solution of a linear equation is known as Moore – Penrose Pseudoinverse of a matrix. Moore – Penrose inverse… Read More »