scikit learn | scikit-learn: machine learning in Python

Keyword	CPC	PCC	Volume	Score	Length of keyword
scikit learn	0.13	1	8327	56	12
scikit	1.83	0.7	4696	20	6
learn	1.57	0.5	5507	54	5

Keyword	CPC	PCC	Volume	Score
scikit learn	1.33	0.9	4654	73
scikit learn pca	0.85	0.1	692	16
scikit learn pdf	0.28	1	2464	7
scikit learn linear regression	0.37	0.8	1636	52
scikit learn svm	1.21	0.8	2649	49
scikit learn knn	0.43	0.8	2701	92
scikit learn python	0.17	0.6	8023	87
scikit learn install	0.38	0.5	3383	19
scikit learn train test split	1.12	0.8	5782	4
scikit learn pipeline	0.26	0.1	1235	53
scikit learning	0.7	0.7	1532	1
scikit learn standardscaler	0.98	0.3	9769	20
scikit learn tutorial	0.96	0.9	3558	14
scikit learn confusion matrix	1.91	0.7	9170	14
scikit learn cheat sheet	0.28	0.7	5317	64
scikit learn metrics	1.95	0.5	9558	32
scikit learn xgboost	1.34	0.8	978	90
scikit learn svc	0.8	1	4224	33
scikit learn pypi	0.74	0.7	7330	32
scikit learn import	1.29	0.5	1911	46
scikit learn gpu	0.89	0.2	8949	37
scikit learn random forest regressor	0.5	1	5895	21
scikit learn one hot encoding	1.58	0.8	5870	61
scikit learn scaler	0.53	0.4	167	18
scikit learn version	0.36	0.2	5459	35

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scikit-learn: machine learning in Python — scikit-learn 1.4.2 …
scikit-learn.org:443

https://scikit-learn.org:443/stable/index.html

WEBMachine Learning in Python. Getting Started Release Highlights for 1.4 GitHub. Simple and efficient tools for predictive data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable - …

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Getting Started — scikit-learn 1.4.2 documentation
scikit-learn.org:443

https://scikit-learn.org:443/stable/getting_started.html

WEBScikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities.

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scikit-learn Tutorials — scikit-learn 1.4.2 documentation
scikit-learn.org:443

https://scikit-learn.org:443/stable/tutorial/index.html

WEBWelcome to scikit-learn; scikit-learn Tutorials. An introduction to machine learning with scikit-learn; A tutorial on statistical-learning for scientific data processing; Working With Text Data; Choosing the right estimator; External Resources, Videos and Talks; Getting Started; User Guide; Glossary of Common Terms and API Elements; Examples ...

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Installing scikit-learn — scikit-learn 1.4.2 documentation
scikit-learn.org:443

https://scikit-learn.org:443/stable/install.html

WEBInstalling the latest release ¶. Operating System Windows macOS Linux. Packager pip conda. Install the 64bit version of Python 3, for instance from https://www.python.org. Then run: pip install -U scikit-learn. In order to check your installation you can use.

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scikit-learn: machine learning in Python - GitHub
github.com:443

https://github.com:443/scikit-learn/scikit-learn

WEBscikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed.

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An introduction to machine learning with scikit-learn
scikit-learn.org:443

https://scikit-learn.org:443/stable/tutorial/basic/tutorial.html

WEBAn introduction to machine learning with scikit-learn. ¶. Section contents. In this section, we introduce the machine learning vocabulary that we use throughout scikit-learn and give a simple learning example.

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Welcome to scikit-learn — scikit-learn 1.4.2 documentation
scikit-learn.org:443

https://scikit-learn.org:443/stable/preface.html

WEBWelcome to scikit-learn. Installing scikit-learn; Frequently Asked Questions; Support; Related Projects; About us; Who is using scikit-learn? Release History; Roadmap; Scikit-learn governance and decision-making; scikit-learn Tutorials; Getting Started; User Guide; Glossary of Common Terms and API Elements; Examples; API Reference; Developer ...

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User guide: contents — scikit-learn 1.4.2 documentation
scikit-learn.org:443

https://scikit-learn.org:443/stable/user_guide.html

WEB1. Supervised learning. 1.1. Linear Models. 1.2. Linear and Quadratic Discriminant Analysis. 1.3. Kernel ridge regression. 1.4. Support Vector Machines. 1.5. Stochastic Gradient Descent. 1.6. Nearest Neighbors. 1.7. Gaussian Processes. 1.8. Cross decomposition. 1.9. Naive Bayes. 1.10. Decision Trees. 1.11.

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scikit-learn · PyPI
pypi.org:443

https://pypi.org:443/project/scikit-learn/

WEBApr 9, 2024 · Latest version. Released: Apr 9, 2024. A set of python modules for machine learning and data mining. Project description. scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

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1. Supervised learning — scikit-learn 1.4.2 documentation
scikit-learn.org:443

https://scikit-learn.org:443/stable/supervised_learning.html

WEB1. Supervised learning ¶. 1.1. Linear Models. 1.1.1. Ordinary Least Squares. 1.1.2. Ridge regression and classification. 1.1.3. Lasso. 1.1.4. Multi-task Lasso. 1.1.5. Elastic-Net. 1.1.6. Multi-task Elastic-Net. 1.1.7. Least Angle Regression. 1.1.8. LARS Lasso. 1.1.9. Orthogonal Matching Pursuit (OMP) 1.1.10. Bayesian Regression. 1.1.11.

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