Omkar2118/datasets huggingface dataset:
KKBox

The task is to predict the chances of a user listening to a song repetitively after the first observable listening event within a time window was triggered. If there are recurring listening event(s) triggered within a month after the user's very first observable listening event, its target is marked 1, and 0 otherwise in the training set. KKBox provides a training data set consists of information of the first observable listening event for each unique user-song pair within a specific time duration. Metadata of each unique user and song pair is also provided. The train and the test data are selected from users listening history in a given time period, and are split based on time. Note that only the labeled train set of the dataset is used for benchmarking.
KFall Dataset

The aim of KFall dataset is to contribute technology development for elderly fall detection and injury prevention. It was acquired by 32 young subjects with 21 types of activities of daily living (ADLs) and 15 types of falls from an inertial sensor attached on low back. In total, it contains 5075 motion files with 2729 ADL motions and 2346 fall motions. In addition, for each fall motion, ready-to-use fall labels (fall initialization and fall impact moment) based on synchronized video references were also included.