COMPANY: CODTECH IT SOLUTIONS
NAME: HARSHIT KUMAR MODI
INTERN ID: CT04DN455
DOMAIN: DATA SCIENCE
DURATION: 4 WEEKS
MENTOR: NEELA SANTOSH
DESCRIPTION OF THE PROJECT:
END-TO-END DATA SCIENCE PROECT
📌 Overview This project is a complete end-to-end data science pipeline, from data preprocessing and model training to API deployment using Flask. It focuses on predicting whether a patient is likely to have diabetes based on medical diagnostic features. The solution includes:
Data Cleaning and Preprocessing
Model Training using Random Forest Classifier
Model Serialization (.pkl file)
API Development with Flask
Optional Web Deployment using Render
This project showcases the practical workflow of a real-world machine learning application—from raw data to a production-ready prediction API.
📈 Problem Statement Build a machine learning model to predict the onset of diabetes based on diagnostic features (e.g., glucose level, blood pressure, BMI, etc.), and serve this model through a REST API that can be consumed by frontend applications, mobile apps, or other systems.
⚙️ Pipeline Workflow
- 📊 Data Preprocessing Handle missing values
Standardize numerical features
Apply one-hot encoding to categorical variables (if any)
Split data into training and testing sets
- 🤖 Model Building Use RandomForestClassifier from scikit-learn
Train the model on the cleaned dataset
Evaluate model accuracy
Save the trained model using joblib
- 🚀 API Development Build a Flask API with a /predict endpoint
Accept JSON input with 8 patient features:
Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age
Return a prediction (0: No diabetes, 1: Diabetes)
- ☁️ Optional Deployment Host the API on Render.com
Publicly accessible via a POST request
✅ Features End-to-end ML pipeline: preprocessing → modeling → API
Modular and easy-to-read Python code
Model ready for production use
Clean and documented API for prediction
Deployable on cloud platforms like Render or Heroku
🧑💻 Technologies Used Python 3.x
pandas – Data manipulation
scikit-learn – Machine learning & preprocessing
joblib – Model serialization
Flask – Web API framework
Render – (Optional) Free cloud deployment
OUTPUT:
