Visualizing the clinical data of diabetes using data science and machine learning algorithms

Abstract

In recent decades Machine learning and Data Science are providing best ways to analyze and solve various problems. In fact, those Machine Learning algorithms gives the best and optimized solutions. These methods are playing key role in providing efficient solutions for the health care problems like predicting the diseases in early stage, and even some automated systems run by Machine Learning Algorithms are prescribing medicines based on the patient’s symptoms. Diabetes is one among the chronic diseases from past years, which leads to the damage of patients eyes, nerves, heart and kidneys etc., In this project we are going to create a pipeline in which the data collected from the source is undergone through some preprocessing techniques and the Machine Learning Algorithms like SVM, KNN, Gradient Boasting, logistic regression and Random Forest are used to classify whether the patient is diabetic or not and the accuracy of these algorithms was measured by using some Evaluation methods like Train/Test Split. Finally, these data will be visualized by using Visualization Tools.