TABLE OF CONTENTS

1
Introduction & Problem Statement
2
Project Architecture & Overview
3
Data Ingestion & ETL Pipeline
4
Data Validation & Schema
5
Data Transformation Techniques
6
Model Selection & Training
7
Model Evaluation & Metrics
8
MLflow Experiment Tracking
9
Containerization & CI/CD
10
AWS Cloud Deployment
11
Skills & Technologies Used
12
Conclusion & Future Work
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