라이브러리
사이킷런(Scikit-learn)
- Classification(분류)
- Regression(회귀)
- Clustering(군집화)
- Dimensionality reduction(차원 축소)
- Model selection(모델 선택)
- Preprocessing(전처리)
https://scikit-learn.org/stable/
scikit-learn: machine learning in Python — scikit-learn 1.1.1 documentation
Model selection Comparing, validating and choosing parameters and models. Applications: Improved accuracy via parameter tuning Algorithms: grid search, cross validation, metrics, and more...
scikit-learn.org
https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html
Choosing the right estimator
Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are better suited for different types of data and different problem...
scikit-learn.org
https://github.com/amueller/odscon-2015
GitHub - amueller/odscon-2015: Slides and material for open data science
Slides and material for open data science. Contribute to amueller/odscon-2015 development by creating an account on GitHub.
github.com