DataOps for Water Quality Classification: Predicting Potability
Overview:
This repository contains a machine learning project aimed at predicting the potability of water based on quality-related measurements. The primary objective is to determine whether water samples are suitable for human consumption. Additionally, the project explores the identification of the most relevant variables for water classification.
Dataset:
The dataset used in this project contains measurements and evaluations of water quality related to potability. Each row in the dataset represents a water sample with specific variables, and the "Potability" column indicates whether the water is suitable for consumption.
Objective:
The primary goal of this project is to develop a machine learning model capable of accurately classifying water samples as potable or non-potable. Additionally, we aim to identify the key variables that influence this classification.
Deployment:
Please note that the deployment of the model is currently in progress, and it will be hosted using AWS (Amazon Web Services) resources.
Stay tuned for updates on the deployment process and further improvements to the project.