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scikit-learn 1.3.2
Other versions

Please cite us if you use the software.

# scikit-learn Tutorials

- An introduction to machine learning with scikit-learn
  - Machine learning: the problem setting
  - Loading an example dataset
  - Learning and predicting
  - Conventions
- A tutorial on statistical-learning for scientific data processing
  - Statistical learning: the setting and the estimator object in scikit-learn
  - Supervised learning: predicting an output variable from high-dimensional observations
  - Model selection: choosing estimators and their parameters
  - Unsupervised learning: seeking representations of the data
  - Putting it all together
- Working With Text Data
  - Tutorial setup
  - Loading the 20 newsgroups dataset
  - Extracting features from text files
  - Training a classifier
  - Building a pipeline
  - Evaluation of the performance on the test set
  - Parameter tuning using grid search
  - Exercise 1: Language identification
  - Exercise 2: Sentiment Analysis on movie reviews
  - Exercise 3: CLI text classification utility
  - Where to from here
- Choosing the right estimator
- External Resources, Videos and Talks
  - New to Scientific Python?
  - External Tutorials
  - Videos

Note

Doctest Mode

The code-examples in the above tutorials are written in a python-console format. If you wish to easily execute these examples in IPython, use:

    %doctest_mode

in the IPython-console. You can then simply copy and paste the examples directly into IPython without having to worry about removing the >>> manually.