Implement an end-to-end MLOps data science project, from initial setup to deployment on AWS EC2 using GitHub Actions. Learn to create a GitHub repository, structure the project using templates, set up logging, perform data ingestion, validation, and transformation, train models, build prediction pipelines, and deploy the solution. Gain hands-on experience with MLflow for experiment tracking and model management throughout the development process.
Overview
Syllabus
Introduction to Project
Create a Repository In Github Account
Create Structure Using Template.py
Implementing Setup.py
Logging Implementation
Data Ingestion
Data Validation
Data Transformation
Model Trainer
Prediction Pipeline
Deployment In EC2 with app runner
Taught by
Krish Naik
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