R

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications

Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more.

Solve real-world data problems with R and machine learning

Build efficient forecasting models using traditional time series models and machine learning algorithms.

A comprehensive guide in developing and deploying high performance microservices with Rust

Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills

Explore the world of neural networks by building powerful deep learning models using the R ecosystem

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data

Explore supervised machine learning with R by studying popular real-world uses cases such as object detection in driverless cars, customer churn, and default prediction

Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages