Data Science
Predict the onset of diabetes based on diagnostic data
Apply Supervised Machine Learning algorithms to accurately predict the onset of diabetes in patients based on their diagnostic data. 
About this Menternship
St James School of Medicine is an international medical school with two campuses in the Caribbean islands. Practicing medicine is much more than textbook knowledge and St James understands that very well. They instill the ability to professionally deal with the ethical, legal and economic realities of 21st century medicine, in their students. They believe compassion is as important as competency in practicing medicine. They are one of the elite organisations who have been accredited by both the principal accrediting organisations in the Caribbean.

Did you know 72.9 million people in India had diabetes as of 2017? Alarming as the number is, it is expected to be 134 million by 2045. Early and accurate diagnosis goes a long way in preserving the health and quality of life of the patient. This is where machine learning can be of help. Machine learning has been applied to many aspects of the medical field. Using it to predict diabetes based on a person’s regular physical examination data, can enable patients and doctors to better deal with this chronic illness.

In this menternship you will build a classification model which will predict the onset of diabetes with high accuracy.

Why take up this Menternship?
On completing this Menternship, you will learn about
You will explore: 
Supervised Machine Learning
Feature Engineering

You will apply:
Data cleaning
Data Visualisation
Model Building 
Model Evaluation

You will create:
A classification model to predict the onset of diabetes based on the Pima Indians Diabetes Database. 

Expected Output
  1. Python Notebook with properly commented code segments for the EDA.
  2. Final Output code with properly commented codes and markdown wherever needed - Git Repository
  3. Report about predictive model building process
  4. Submit your video
Predict the onset of diabetes based on diagnostic data
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