Deep Learning in R – MNIST Classifier with Keras In a day and age where everyone seems to know how to solve at least basic deep learning tasks with Python, one question arises: How does R fit into the whole deep learning picture? You don’t need deep learning algorithms to ...

Gradient Boosting with R Gradient boosting is one of the most effective techniques for building machine learning models. It is based on the idea of improving the weak learners (learners with insufficient predictive power). Do you want to learn more about machine learning with R? Check our complete guide to ...

Build an MNIST Classifier With Random Forests Simple image classification tasks don’t require deep learning models. Today you’ll learn how to build a handwritten digit classifier from scratch with R and Random Forests and what are the “gotchas” in the process. Are you completely new to machine learning? ...

Decision Trees with R Decision trees are among the most fundamental algorithms in supervised machine learning, used to handle both regression and classification tasks. In a nutshell, you can think of it as a glorified collection of if-else statements, but more on that later. Interested in more basic machine learning ...

Pandas vs. dplyr It’s difficult to find the ultimate go-to library for data analysis. Both R and Python provide excellent options, so the question quickly becomes “which data analysis library is the most convenient”. Today’s article aims to answer this question, assuming you’re equally skilled in both ...

Exploratory Data Analysis With dplyr When it comes to data analysis in R, you should look no further than the dplyr package. It’s an excellent all-rounder – providing you with extensive drill-down abilities while keeping the coding clean and minimal. Are you completely new to R? Check out what you ...

REST APIs with R and Plumber REST APIs are everywhere around us. Software engineers use them to develop backend logic, and data scientists use them to deploy machine learning models. Today you’ll learn how to make a basic REST API with R and the plumber package. Completely new to ...

Logistic Regression with R Logistic regression is one of the most fundamental algorithms from statistics, commonly used in machine learning. It’s not used to produce SOTA models but can serve as an excellent baseline for binary classification problems. Interested in machine learning for beginners? Check our detailed guide on ...

Datasets often require many work hours to understand fully. R makes this process as easy as possible through the dplyr package – the easiest solution for code-based data analysis. You’ll learn how to use it today. Are you completely new to R? Here’s our beginner R guide for programmers. ...

Geo maps with R and Leaflet Data visualization can be tough to get right, and geospatial data is not an exception. Today you’ll learn how to build aesthetically pleasing interactive maps with R and leaflet.  Having problems with basic R visualizations? Here’s our guide for building stunning scatter ...

Linear Regression with R Chances are you had some prior exposure to machine learning and statistics. Basically, that’s all linear regression is – a simple statistics problem.  Need help with Machine Learning solutions? Reach out to Appsilon. Today you’ll learn the different types of linear regression and how to ...

Scatter Plots with R Do you want to make stunning visualizations, but they always end up looking like a potato? It’s a tough place to be. Luckily, R makes it easy to produce great-looking visuals. Today you’ll learn how to create impressive scatter plots with R and the ...

Accuracy can be misleading. These 3 alternatives can't. The post Top 3 Classification Machine Learning Metrics – Ditch Accuracy Once and For All appeared first on Better Data Science.