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This article covers how and when to use  k-nearest neighbors classification with scikit-learn. Focusing on concepts, workflow, and examples. We also cover distance metrics and how to select the best value for k using cross-validation.

K-Nearest Neighbors (KNN) Classification with scikit-learn 

In this tutorial, learn Decision Tree Classification, attribute selection measures, and how to build and optimize Decision Tree Classifier using Python Scikit-learn package.

Decision Tree Classification in Python Tutorial 

Learn about data augmentation techniques, applications, and tools with a TensorFlow and Keras tutorial.  

A Complete Guide to Data Augmentation

簡單易懂的 scikit-learn 教學，適合想要使用 Python 實作機器學習的初學者閱讀。

Scikit-Learn 教學：Python 與機器學習

You can preprocess the heck out of your data but the proof is in the pudding: how well does your model then perform?

Preprocessing in Data Science (Part 3): Scaling Synthesized Data

Discover whether centering and scaling help your model in a logistic regression setting.

Preprocessing in Data Science (Part 2): Centering, Scaling and Logistic Regression

This article will explain the importance of preprocessing in the machine learning pipeline by examining how centering and scaling can improve model performance.

Machine Learning Tutorial

Scikit-Learn 教學：Python 與機器學習

Preprocessing in Data Science (Part 3): Scaling Synthesized Data

Preprocessing in Data Science (Part 2): Centering, Scaling and Logistic Regression

Preprocessing in Data Science (Part 1): Centering, Scaling, and KNN