Smokers-Classification

A repository of implemented ML Algorithms to classification smokers from multivariate data.
As part of the process of learning the research problem and the data, a preliminary file of EDA is also attached.
The task was given as part of a ML course at the university.

The subtasks given as part of the task:
1) Performing a pre-processing process on the data, handling NaN data and values at the edges, learning the most significant features, examining distributions of variables in the data, performing discretization and categorization.
2) Application of 2 Supervised ML models - NN & Decision Tree, while adjusting the hyper parameters with the help of Grid-Search. Using Naptune.ai for monitoring.
3) Application of K-Means clustering.
4) Application of Un-supervised model with the help of integration and pre-training of NN and then application of Voting Classifier and create ensemble model.