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Flask API including ML model Deployment(PCA, XGBoost and Ensemble Learning)

Welcome to the ML model deployment project showcasing the integration of machine learning models using PCA and XGBoost in Python. This Flask API allows users to receive real-time predictions by sending data from their mobile devices.

Overview

This project deploys machine learning models, incorporating Principal Component Analysis (PCA) and XGBoost, within a Flask API. Serialized using pickle, the models are seamlessly integrated into the API, enabling users to make predictions on-the-fly.

Key Features

  • PCA and XGBoost Models: Utilizes PCA for dimensionality reduction and XGBoost for efficient machine learning predictions.

  • Flask API Integration: Models are integrated into a Flask API, providing a user-friendly interface for real-time predictions.

  • Mobile Device Compatibility: Users can send data from their mobile devices to the Flask API, receiving prompt predictions.