Kai R. Larsen

Daniel S. Becker

What is machine learning? -- Automating machine learning -- Specify business problem -- Acquire subject matter expertise -- Define prediction target -- Decide on unit of analysis -- Success, risk, and continuation -- Accessing and storing data -- Data integration -- Data transformations -- Summarization -- Data reduction and splitting -- Startup processes -- Feature understanding and selection -- Build candidate models -- Understanding the process -- Evaluate model performance -- Comparing model pairs -- Interpret model -- Communicate model insights -- Set up prediction system -- Document modeling process for reproducibility -- Create model monitoring and maintenance plan -- Seven types of target leakage in machine learning and an exercise -- Time-aware modeling -- Time-series modeling.

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