In the exercises below we cover the some useful features of data.table ,data.table is a library in R for fast manipulation of large data frame .Please see the data.table vignette before trying the solution .This first set is intended for the begineers of data.table package and does not cover set keywords, joins of data.table which […]

# Exercises (intermediate)

## LASSO regression in R exercises

Least Absolute Shrinkage and Selection Operator (LASSO) performs regularization and variable selection on a given model. Depending on the size of the penalty term, LASSO shrinks less relevant predictors to (possibly) zero. Thus, it enables us to consider a more parsimonious model. In this exercise set we will use the glmnet package (package description: here) […]

## Density-Based Clustering Exercises

Density-based clustering is a technique that allows to partition data into groups with similar characteristics (clusters) but does not require specifying the number of those groups in advance. In density-based clustering, clusters are defined as dense regions of data points separated by low-density regions. Density is measured by the number of data points within some […]

## Neural networks Exercises (Part-1)

Neural network have become a corner stone of machine learning in the last decade. Created in the late 1940s with the intention to create computer programs who mimics the way neurons process information, those kinds of algorithm have long been believe to be only an academic curiosity, deprived of practical use since they require a […]

## Quantile Regression in R exercises

The standard OLS (Ordinary Least Squares) model explains the relationship between independent variables and the conditional mean of the dependent variable. In contrast, quantile regression models this relationship for different quantiles of the dependent variable. In this exercise set we will use the quantreg package (package description: here) to implement quantile regression in R. Answers […]

## A Primer in functional Programming in R (part -2)

In the last exercise, We have seen how powerful functional programming principles can be and how it can drammatically increase the readablity of the code and how easily you can work with them .In this set of exercises we will look at functional programming principles with purrr.Purrr comes with a number of interesting features and […]

## Evaluate your model with R Exercises

There was a time where statistician had to manually crunch number when they wanted to fit their data to a model. Since this process was so long, those statisticians usually did a lot of preliminary work researching other model who worked in the past or looking for studies in other scientific field like psychology or […]

## A Primer in Functional Programming in R (Part – 1)

In the exercises below we cover the basics of functional programming in R( part 1 of a two series exercises on functional programming) . We consider recursion with R , apply family of functions , higher order functions such as Map ,Reduce,Filter in R . Answers to the exercises are available here. If you obtained […]

## Introduction to copulas Exercises (Part-2)

Copulas are a powerful statistical tool commonly used in the finance sector to generate samples from a given multivariate joint distribution. The principal advantage of using those types of function over other methods is that copulas describe the multivariate joint distribution as his margin and the dependence structure between them, which give the user the […]

## Introduction to copulas Exercises (Part-1)

Copulas are a powerful statistical tool commonly used in the finance sector to generate samples from a given multivariate joint distribution. The principal advantage of using those types of function over other methods is that copulas describe the multivariate joint distribution as his margin and the dependence structure between them, which give the user the […]