This End-to-End Machine Learning course will help you with core concepts and advanced MLOps integration. 

You will learn how to:
✨ Conduct thorough EDA to craft compelling data narratives.
✨ Engineer features with a deep understanding of why and how.
✨ Implement a single model with rigorous testing and validation.
✨ Write scalable, defensive, and readable code using design patterns.
✨ Integrate MLOps with tools like ZenML & MLflow for experiment tracking and deployment.

Before starting this project, read this initial doc: https://docs.google.com/document/d/108EMtdWOnXZp5UTKdHYrL9I95CUQf9FfABa1Wh-vEM8/edit

You can buy the source code here: https://topmate.io/ayush_singh13/1192098 

Course developed by @AyushSinghSh

freeCodeCamp is a nonprofit organization offering free online coding courses and programming tutorials, covering topics such as web development, data science, and machine learning. Learners can gain practical coding skills, build real-world projects, and earn certifications to advance their careers in tech.

freeCodeCamp

The post provides a comprehensive guide on undertaking an end-to-end machine learning project focused on house price prediction. It delves into core machine learning concepts, data analysis, feature engineering, and model implementation with robust testing. Additionally, it emphasizes MLOps integrations using tools like ZenML and MLFlow for experiment tracking and deployment. The tutorial also underscores the importance of writing scalable and readable code by employing design patterns such as Factory and Strategy patterns. The project aims to differentiate itself by focusing on thorough data understanding and robust implementation practices, promising to enhance one's data science portfolio and career prospects.

End-to-End Machine Learning Project – AI, MLOps