scikit-learn 指南

• 使用scikit-learn进行机器学习的简介
  • 机器学习：问题设置
  • 加载样例数据集
  • 学习和预测
  • 模型持久化
  • 惯例约定
• 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
  • Finding help
• 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

注解

Doctest 模式

以上指南中的代码例子是用*python-console*的格式来编写的。如果你想便于在**IPython**中运行这些例子，使用:

%doctest_mode

在IPython-console中。接下来你可以简单地直接把例子复制、粘贴到IPython中，而不需担心要手动删掉**>>>**。