Differential equations play an important role in biology, chemistry, physics, engineering, economy, and other disciplines. In R they can be solved numerically with a few lines of code, and several packages support solving them. We will demonstrate this with some easy, but interesting examples.

We will shortly repeat what we learned about the 'mlr3' package last year. A quick look at the 'mlpack' package and on AdaBoosting in general. Then there is 'tabnet', a package relying on PyTorch and providing deep neural network technology for tabular data.

Discusses several CRAN packages that provide key-value stores.

Application of linear regression tree models 'lmtree()' and 'cubist()' to Boston Housing Data.

An overview of nonlinear Regression in Base R and packages.

Subgroup Discovery is a technique for descriptive Data Mining.

Find numbers of length r that obey certain divisibility rules.

Find Hamiltonian paths and solve the puzzle with the help of R.