https://github.com/rasgointelligence/feature-engineering-tutorials
Data Science Feature Engineering and Selection Tutorials
https://github.com/rasgointelligence/feature-engineering-tutorials
data-cleaning data-science exploratory-data-analysis feature-engineering feature-selection features jupyter machine-learning notebook pandas pandas-profiling pyrasgo python scikit-learn sweetviz tutorial tutorials xgboost
Last synced: 10 days ago
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Data Science Feature Engineering and Selection Tutorials
- Host: GitHub
- URL: https://github.com/rasgointelligence/feature-engineering-tutorials
- Owner: rasgointelligence
- License: agpl-3.0
- Created: 2021-05-07T17:57:05.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2025-02-03T07:20:32.000Z (5 months ago)
- Last Synced: 2025-02-03T08:26:20.339Z (5 months ago)
- Topics: data-cleaning, data-science, exploratory-data-analysis, feature-engineering, feature-selection, features, jupyter, machine-learning, notebook, pandas, pandas-profiling, pyrasgo, python, scikit-learn, sweetviz, tutorial, tutorials, xgboost
- Language: Jupyter Notebook
- Homepage: https://www.rasgoml.com/
- Size: 2.76 MB
- Stars: 279
- Watchers: 9
- Forks: 100
- Open Issues: 32
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Tutorials: Feature Engineering in Python
[](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main) [](https://forum.rasgoml.com/) [](https://join.slack.com/t/rasgousergroup/shared_invite/zt-nytkq6np-ANEJvbUSbT2Gkvc8JICp3g)Andrew Ng stated, “applied ML is basically just feature engineering.” In data science and ML, the most important, but oftentimes most overlooked, piece of the puzzle is feature engineering.
At [Rasgo](https://www.rasgoml.com/), we are data scientists on the mission to enable the global data science community to generate valuable and trusted insights from data in under 5 minutes. As we have marched forward on this mission, we’ve grown incredibly frustrated in the lack of helpful content and python functions that target feature engineering. We wrestle with these problems everyday and we wanted to provide a repository of recipes that showcase how to use the best tools available in this space. Additionally, we’ve built our own SDK ([PyRasgo](https://github.com/rasgointelligence/pyrasgo/blob/main/tutorials/PyRasgo%20Tutorial.ipynb)) for feature engineering that enables users to automatically track, visualize, and evaluate their feature engineering experiments to make more accurate and explainable feature engineering decisions.
In that vein, this repository contains tutorials and code to enable data scientists to easily create new ML features and evaluate their importance for supervised machine learning. We sincerely hope this is helpful and please leave comments with any questions on what we can do to improve!
Please join us on the
* [Rasgo Forum](https://forum.rasgoml.com) for questions about these recipies and PyRasgo.
* [Rasgo User Group Slack](https://join.slack.com/t/rasgousergroup/shared_invite/zt-nytkq6np-ANEJvbUSbT2Gkvc8JICp3g) to join our community.
* Video Tutorials on YouTube _(Coming Soon)_## Table of Contents
* Feature Profiling
* [pandas-profiling](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-profiling/pandas-profiling.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-profiling/pandas-profiling.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-profiling/pandas-profiling.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-profiling/pandas-profiling.ipynb)
* [SweetViz](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-profiling/SweetViz-profiling.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-profiling/SweetViz-profiling.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-profiling/SweetViz-profiling.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-profiling/SweetViz-profiling.ipynb)
* Data Cleaning
* Missing Data
* [pandas](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-missing-data.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-missing-data.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-missing-data.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=data-cleaning/pandas-missing-data.ipynb)
* Duplicate Data
* [pandas](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-duplicate-data.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-duplicate-data.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-duplicate-data.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=data-cleaning/pandas-duplicate-data.ipynb)
* Data Type Mismatch
* [pandas](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-data-type-mismatch.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-data-type-mismatch.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-data-type-mismatch.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=data-cleaning/pandas-data-type-mismatch.ipynb)
* Date Gaps in Time Series
* [pandas](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-date-gaps.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-date-gaps.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/data-cleaning/pandas-date-gaps.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=data-cleaning/pandas-date-gaps.ipynb)
* Feature Transformation
* Time-series
* [Lag](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-lag.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-lag.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-lag.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-lag.ipynb)
* [Moving Average](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-moving-average.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-moving-average.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-moving-average.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-moving-average.ipynb)
* [Weekly Resampled Aggregation](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-aggregate-weekly.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-aggregate-weekly.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-aggregate-weekly.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-aggregate-weekly.ipynb)
* [Weekly Rolling Aggregation](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-aggregate-rolling-weekly.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-aggregate-rolling-weekly.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-aggregate-rolling-weekly.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-aggregate-rolling-weekly.ipynb)
* [Velocity and Acceleration](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-velocity-acceleration.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-velocity-acceleration.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-velocity-acceleration.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-velocity-acceleration.ipynb)
* [Energy](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-energy.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-energy.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-energy.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-energy.ipynb)
* [Mean Difference](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-mean-difference.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-mean-difference.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-mean-difference.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-mean-difference.ipynb)
* [Mean Absolute Difference](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-mean-absolute-difference.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-mean-absolute-difference.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/pandas-mean-absolute-difference.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/pandas-mean-absolute-difference.ipynb)
* [tsfresh](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/tsfresh.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/tsfresh.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/time-series/tsfresh.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/time-series/tsfresh.ipynb)
* Categorical
* [One-hot encoding](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/one-hot-encoding.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/one-hot-encoding.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/one-hot-encoding.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/categorical/one-hot-encoding.ipynb)
* [Target encoding](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/target-encoding.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/target-encoding.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/target-encoding.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/categorical/target-encoding.ipynb)
* [Leave One Out encoding](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/leave-one-out-encoding.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/leave-one-out-encoding.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/categorical/leave-one-out-encoding.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/categorical/leave-one-out-encoding.ipynb)
* Numerical
* [Standard scaler](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/standard-scaler.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/standard-scaler.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/standard-scaler.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/numerical/standard-scaler.ipynb)
* [Min-Max scaler](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/min-max-scaler.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/min-max-scaler.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/min-max-scaler.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/numerical/min-max-scaler.ipynb)
* [Robust scaler](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/robust-scaler.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/robust-scaler.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-transformation/numerical/robust-scaler.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-transformation/numerical/robust-scaler.ipynb)
* Model Selection
* Train-Test Split
* Time Series Split
* [Scikit-learn](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-time-series-split.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-time-series-split.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-time-series-split.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/sklearn-time-series-split.ipynb)
* [Train-Test Split](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-train-test-split.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-train-test-split.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-train-test-split.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/sklearn-train-test-split.ipynb)
* K-Fold or Cross-Validation
* [Random](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-cross-validation-split.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-cross-validation-split.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-cross-validation-split.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/sklearn-cross-validation-split.ipynb)
* [Stratified](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-stratified-cross-validation-split.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-stratified-cross-validation-split.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-stratified-cross-validation-split.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/sklearn-stratified-cross-validation-split.ipynb)
* [Group](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-group-cross-validation-split.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-group-cross-validation-split.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/sklearn-group-cross-validation-split.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/sklearn-group-cross-validation-split.ipynb)
* Model Comparison
* [PyCaret](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-comparison/pycaret-comparison.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-comparison/pycaret-comparison.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-comparison/pycaret-comparison.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-comparison/pycaret-comparison.ipynb)
* Model Training
* Catboost
* [Classification](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-training/catboost-classification.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-training/catboost-classification.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-training/catboost-classification.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-training/catboost-classification.ipynb)
* [Regression](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-training/catboost-regression.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-training/catboost-regression.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-training/catboost-regression.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-training/catboost-regression.ipynb)
* Model Metrics
* Binary Classification
* [AUC](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-categorical-AUC.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-categorical-AUC.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-categorical-AUC.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-metrics/catboost-categorical-AUC.ipynb)
* [Log Loss](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-categorical-logloss.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-categorical-logloss.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-categorical-logloss.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-metrics/catboost-categorical-logloss.ipynb)
* Regression
* [MAE](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-mae.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-mae.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-mae.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-metrics/catboost-regression-mae.ipynb)
* [MAPE](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-mape.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-mape.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-mape.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-metrics/catboost-regression-mape.ipynb)
* [RMSE](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-rmse.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-rmse.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-rmse.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-metrics/catboost-regression-rmse.ipynb)
* [R^2](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-r2.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-r2.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/model-selection/model-metrics/catboost-regression-r2.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=model-selection/model-metrics/catboost-regression-r2.ipynb)
* Feature Importance
* [Scikit-learn](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/Sklearn%20Feature%20Importance.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/Sklearn%20Feature%20Importance.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/Sklearn%20Feature%20Importance.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-importance/Sklearn%20Feature%20Importance.ipynb)
* [XGBoost](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/XGBoost%20Feature%20Importance.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/XGBoost%20Feature%20Importance.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/XGBoost%20Feature%20Importance.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-importance/XGBoost%20Feature%20Importance.ipynb)
* [catboost](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/Catboost%20Feature%20Importance.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/Catboost%20Feature%20Importance.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-importance/Catboost%20Feature%20Importance.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-importance/Catboost%20Feature%20Importance.ipynb)
* Feature Selection
* Model Agnostic
* [Low Variance](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/Low%20Variance.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/Low%20Variance.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/Low%20Variance.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-agnostic/Low%20Variance.ipynb)
* Univariate Feature Selection
* [F-test](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/F%20Test.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/F%20Test.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/F%20Test.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-agnostic/F%20Test.ipynb)
* [Mutual Information](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/Mutual%20Information.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/Mutual%20Information.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-agnostic/Mutual%20Information.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-agnostic/Mutual%20Information.ipynb)
* Model Based
* Lasso-based Selection _(Coming soon)_
* Feature Importance
* [Scikit-learn Tree-based](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-gini.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-gini.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-gini.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-based/sklearn-feature-selection-gini.ipynb)
* [Permutation Importance](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-permutation.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-permutation.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-permutation.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-based/sklearn-feature-selection-permutation.ipynb)
* [SHAP Values](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-shap.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-shap.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-feature-selection-shap.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-based/sklearn-feature-selection-shap.ipynb)
* Sequential Feature Selection
* Forward Stepwise Selection _(Coming soon)_
* Backwards Stepwise Selection
* [Scikit-learn Tree-based](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sequential-feature-selection/sklearn-backward-stepwise-selection.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sequential-feature-selection/sklearn-backward-stepwise-selection.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sklearn-backward-stepwise-selection.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-based/sequential-feature-selection/sklearn-backward-stepwise-selection.ipynb)
* [catboost](https://github.com/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sequential-feature-selection/catboost-backward-stepwise-selection.ipynb): [](https://colab.research.google.com/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sequential-feature-selection/catboost-backward-stepwise-selection.ipynb) [](https://nbviewer.jupyter.org/github/rasgointelligence/feature-engineering-tutorials/blob/main/feature-selection/model-based/sequential-feature-selection/catboost-backward-stepwise-selection.ipynb) [](https://mybinder.org/v2/gh/rasgointelligence/feature-engineering-tutorials/main?filepath=feature-selection/model-based/sequential-feature-selection/catboost-backward-stepwise-selection.ipynb)