The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest […]

Our case study is a bank that wants to develop a churn model to predict the probability of a customer to churn. The banking sector has become one of the main industries in developed countries. The technical progress and the increasing number of banks raised the level of competition. Banks are working hard to survive […]

Data from IBM Watson tutorials.

Predict if a new client is going to get a loan or not based on historical data.

The aim is to find whether or not a person has heart disease based on information about their health.

Let´s prepare a simple example where we can verify that Dataslayer ML learns from a predefined data logic. The ML will discover this logic.

An individual’s annual income results from various factors. Intuitively, it is influenced by the individual’s education level, age, gender, occupation, and etc.

Detect if a tumour is benign or malignant.

The Titanic dataset is a compilation of data from the ship’s passengers. These features range from age, gender to class cabin. There is also a column in the dataset where passengers are classified as ‘Survived’ or ‘Not survived’ from the sink. The RMS Titanic sank in the North Atlantic Ocean in the early hours of […]