Explore an end-to-end machine learning project with deployment, covering problem statement formulation, exploratory data analysis (EDA), and model training. Learn to handle exceptions, implement logging, perform feature engineering, and use Git for version control. Follow along with provided code examples and gain practical insights into developing and deploying a complete machine learning solution.
End to End ML Project With Deployment - Project Problem Statement, EDA and Model Training
Krish Naik via YouTube
Overview
Syllabus
Exception Handling Logger code
Problem Statement
EDA And Feature Engineering
Model Training
Git Commit
Taught by
Krish Naik
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