I’d like to work side-by-side with an experienced Machine Learning Engineer who can teach me each stage of a complete ML pipeline while we actually build one together. As a beginner, I need concepts broken down clearly and the “why” behind every decision explained, not just the code itself. Scope • Choose or source a small, manageable dataset. • Walk me through data cleaning and exploratory analysis in Python (pandas, matplotlib, seaborn). • Build and tune at least one supervised model in scikit-learn or a comparable library, discussing metrics and trade-offs. • Package the final model and show me a basic deployment path—CLI script, Flask API, or simple cloud option—so I see the end-to-end flow. • Throughout, share best practices for version control, virtual environments, and reproducibility. Format Live screen-share sessions plus concise takeaway notes and commented notebooks/scripts after each meeting suit me best. I’m happy to schedule multiple short sessions instead of one marathon call. Outcome By project end I should be comfortable repeating the full workflow on my own, confident in both the tools and the underlying reasoning. If you’re patient, love teaching, and are fluent in Python’s ML stack, let’s get started!