End to End Machine Learning

Hospital readmission rates for certain conditions such as diabetes are now considered an indicator of hospital quality and also have a negative impact on the cost of care. We used the medical dataset available on the UCI website to find the best models that can help predict the readmission of diabetic patients. The stakeholder in this project will be hospital officials who can use the results to determine which patients have the best chances of readmission. This will save millions of money in the hospital and also improve the quality of health care. The first task you are asked to perform is to build a model of Diabetes Readmission Prediction. This data has metrics such as encounter_id, patient_nbr,race, gender, age, weight, admission_type_id, discharge_disposition_id, admission_source_id, time_in_hospital, payer_code, and so on.