End-to-End Machine Learning Project with Python: From Scratch to Deployment 1
In this video, we are diving deep into End-to-End Machine Learning Engineering. We don't just stop at building a model; we focus on the entire lifecycle using Python. 🐍
If you’ve ever wondered how to take a project from a raw dataset to a functional, engineered system, this tutorial is for you! We cover the "Learning Star" approach to building robust, scalable AI solutions.
What we cover in this video:
✅ Environment Setup: Setting up your Python workspace for ML.
✅ Data Engineering: Ingesting and cleaning data for production.
✅ Model Development: Training a model that actually performs.
✅ Engineering the Pipeline: Connecting all the pieces end-to-end.
✅ Deployment Basics: Making your model accessible.
Tools used: Python, Pandas, Scikit-Learn,