machine_learning_basics - Plain python implementations of basic machine learning algorithms

•    Jupyter

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This repository contains implementations of basic machine learning algorithms in plain Python (Python Version 3.6+). All algorithms are implemented from scratch without using additional machine learning libraries. The intention of these notebooks is to provide a basic understanding of the algorithms and their underlying structure, not to provide the most efficient implementations. After several requests I started preparing notebooks on how to preprocess datasets for machine learning. Within the next months I will add one notebook for each kind of dataset (text, images, ...). As before, the intention of these notebooks is to provide a basic understanding of the preprocessing steps, not to provide the most efficient implementations.

machine-learning logistic-regression ipynb machine-learning-algorithms linear-regression perceptron python-implementations kmeans algorithm python3 neural-network k-nearest-neighbours k-nearest-neighbor k-nn neural-networks

interactiveknn - Interactive K-Nearest Neighbors machine learning algorithm in JavaScript.

•    Javascript

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Visually interact with dots in your browser classifying unknown dots using the K-Nearest Neighbors algorithm. Playable at Lettier.com.

interactive-knearest-neighbors knn machine-learning data-science visualization html5 nearest-neighbor-search data-analysis scikit-learn machine-learning-algorithms ai classification statistics gui k-nearest-neighbors k-nearest-neighbor k-nearest-neighbours k-nn nearest neighbors