Table of Contents
- DS/ML Projects – Initial Setup
- ML Projects Lifecycle
- ML Architecture – Framework and Components
- Data Exploration and Quantifying Business Problem
- Training & Testing ML model
- ML model performance measurement
- CRUD operations with different JavaScript frameworks
- Feature Store
- Building ML Pipeline
