Are you interested in guest posting? Publish at DataScience+ via your RStudio editor.CategoryVisualizing DataTagsAutoMLBest R PackageslaresMachine LearningR ProgrammingThe lares package has multiple families of functions to help the analyst or data scientist achieve quality robust analysis without the need of much coding. One of the most complex but valuable ...

This latest update to GooglyPlusPlus2021 includes the following changes a) All the functions in the ‘Batsman’ and ‘Bowler ‘tabs now include a date range, which allows you specify a period of interest. b) The ‘Rank Batsman’ and ‘Rank Bowler’ tabs also include a date range selector, against the earlier version ...

Boxplot in R, we will demonstrate how to make a box plot in the R programming language. A box plot summarises the distribution of numerical data that has been sorted. If you enjoyed our Data Science tutorials, please subscribe to our YouTube Channe...

Boxplot in R, we will demonstrate how to make a box plot in the R programming language. A box plot summarises the distribution of numerical data that has been sorted. If you enjoyed our... The post Boxplot in R Language appeared first on finnstats.

This post implements Black-Derman-Toy (BDT) interest rate tree using R. This implementation is based on the previous post for BDT model. R Implementation of BDT Interest Rate Tree We implement BDT tree according to the content of the previous p...

Learn how to develop from scratch an interactive web interface in R shiny on November 10th. Shiny is the ever more popular approach to share R work, especially to business users without a technical background, but are required to make data-driven de...

Line Plot in R, this tutorial will show you how to create simple line plots, adjust the axis labels and colors of plots, and create multiple line graphs. Line plots aid in the visualization of time series data. Throughout this lesson, you will see ...

Line Plot in R, this tutorial will show you how to create simple line plots, adjust the axis labels and colors of plots, and create multiple line graphs. Line plots aid in the visualization... The post Line Plots in R-Time Series Data Visualization appeared first on finnstats.

Survival analysis and germination/emergence data: an overlooked connection Seed germination and emergence data describe the time until the event of interest occurs and, therefore, they can be put together in the wide group of time-to-event data. Y...

Machine learning projects are a beautiful medley of the code used to build models and the data used to train them. ML models are complex beasts that change through a myriad of methods from the datasets used and the way they’re transformed to the changing of the code itself. ...

Data Visualization with R, In this tutorial, we will describe how to create a scatter plot in the R programming language. “ggplot2” is a fantastic package for making visually appealing data displays. If you... The post Data Visualization with R-Scatter plots appeared first on finnstats.

FairPAN — bringing fairness to neural networksMotivationWith the ongoing development of XAI methods, we — data scientists have to take more and more responsibility for the behaviour of our models. It means that we should no longer care only about what ...

Introduction “There is no unique definition of a square root of a matrix. While there are a few ways to calculate it in closed form, the results differ”. It was from these notes that I read in my multivariate statistics class that inspired me to explore the the geometric interpretations ...

We are conducting another survey to see where u...

People have been telling me not to teach caret anymore, albeit I do teach TidyModels as well. Their argument is that TidyModels is new and shiny and we should be using the most up to date tools. I get this justification, but is caret really dead? My answer is “not ...

Deep Belief Networks (DBN) and Autoencoders, Let’s take a look at DBNs and how they are created on top of RBMs. If you haven’t read the previous posts yet, you can read them by clicking the below links. Introduction to Machine Learning wit...