A Complete Machine Learning Project Walk-Through in Python: Part One by Will Koehrsen

Reading through a data science book or taking a course, it can feel like you have the individual pieces, but don’t quite know how to put them together. Taking the next step and solving a complete machine learning problem can be daunting, but preserving and completing a first project will give you the confidence to tackle any data science problem. This series of articles will walk through a complete machine learning solution with a real-world dataset to let you see how all the pieces come together.

We’ll follow the general machine learning workflow step-by-step:

1. Data cleaning and formatting
2. Exploratory data analysis
3. Feature engineering and selection
4. Compare several machine learning models on a performance metric
5. Perform hyperparameter tuning on the best model
6. Evaluate the best model on the testing set
7. Interpret the model results
8. Draw conclusions and document work

Along the way, we’ll see how each....