The main objective of this project is to predict if a person is having compensated hypothyroid, primary hypothyroid, secondary hypothyroid or negative (no thyroid) with the help of Machine Learning The client will send data in multiple files in batches to a given location. Data will contain different classes of thyroid and 30 columns of different values. “Class” column will have four unique values “negative,compensated_hypothyroid, primary_hypothyroid, secondary_hypothyroid”.

It help’s the client to easily detect the thyroid by 90% accuracy. Deployed this Project for Internship(at Ineuro.ai) (as Freasher) Built a client facing API using streamli flask.

Project Work Flow :

1. Data Ingestion
2. Data Transformation
3. Model clustering
4. Model Selection & Training
5. Model Evaluation
6. Model Deployment

Link To the GitHub Repository

• scene