Body sensors are used to collect information about postures during the realization of an exercise. The different types of postures are encoded in the variable "classe":
- A: correct posture during the exercise
- B, C, D or E: incorrect posture during the exercise
The objective of this project is to analyse the data collected and implement the following Machine Learning models.
- Unsupervised learning: develop a segmentation model that captures the group structure present in the data collected. Compare and evaluate different models.
- Supervised learning: develop a predictive model that predicts the posture during the exercise based on the data collected. Compare and evaluate different models.
Python & R are used to develop the project.
