This project House Prices from Kaggle uses ProjectTemplate package.
As a small test we used Azure ML side by side and ended up doing a large amount of preprocessing in Azure ML Studio. Our experience was a bit mixed, some things are easy others are less straightforward. So for this project we start with the preprocessed file from Azure this included:
- recoding to ordered factors (especially quality assessments)
- simplified feature engineering like 'HasLotFrontage' or 'HasLandContour'
- fix missing values
- convert combined columns constructs like 'Condition1' and 'Condition2' to indicator values
- Normalize data Zscore
- SalePriceLog, MiscValLog
- Some extra small feature engineering like 'HouseDirectSoldAfterBuilt'
- Complete conversion to indicator values has not been applied
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Prepare Problem a) Load libraries b) Load dataset c) Split-out validation dataset
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Summarize Data a) Descriptive statistics b) Data visualizations
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Prepare Data a) Data Cleaning b) Feature Selection c) Data Transforms
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Evaluate Algorithms a) Test options and evaluation metric b) Spot Check Algorithms c) Compare Algorithms
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Improve Accuracy a) Algorithm Tuning b) Ensembles
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Finalize Model a) Predictions on validation dataset b) Create standalone model on entire training dataset c) Save model for later use