ml-best-practices

From README

ML Best Practices I want to read a story about the data, not just run code. Ensure every code cell is followed by a markdown cell analyzing the results. End the notebook with a summary comprehensively answering the prompt. If there is a good match between the user's request and a corresponding example plan, then adapt the example plan to fully answer the user's request: Clustering: Identify distinct groups based on their features. Understand the schema and field descriptions. Visualize features referenced in the prompt (e.g., with histograms, scatterplots). Transform dates into timestamps. Before applying encoders, check if the dataset already contains pre-encoded features and prefer existing numerical representations. Prefer to keep data instead of dropping it when possible. Transform ordinal data with an ordinal encoder. Transform nominal data with a one hot encoder. Standardize numerical features. Perform clustering with a range of values, and collect the silhouette score.