라이브러리

인공지능/참고

by 2^7 2022. 6. 27. 14:36

사이킷런(Scikit-learn)

Classification(분류)
Regression(회귀)
Clustering(군집화)
Dimensionality reduction(차원 축소)
Model selection(모델 선택)
Preprocessing(전처리)

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

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