> For the complete documentation index, see [llms.txt](https://www.parapathology.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.parapathology.com/statistics-and-bioinformatics/machine-learning.md).

# Machine Learning

Algorithms that learn from data, from classical methods (regression, trees, SVM, clustering) through neural networks to large language models and agent skills. Each child note covers one algorithm family with courses and code; the pathology applications of these methods are collected under [Digital Pathology](/computational-digital-and-mathematical-pathology/digital-pathology.md) and [Image Analysis](/computational-digital-and-mathematical-pathology/image-analysis.md).

## Machine Learning

* Fun and Easy Machine Learning Course in Keras and Python

<https://keras.io/>

<https://www.youtube.com/watch?v=RPvLgzEybJU&list=PL_Nji0JOuXg2udXfS6nhK3CkIYLDtHNLp>

* Machine Learning Glossary

<https://developers.google.com/machine-learning/glossary/>

## Large Language Models

* [Stanford CS336: Language Modeling from Scratch — Spring 2026 (YouTube playlist)](https://www.youtube.com/playlist?list=PLoROMvodv4rMqXOcazWaTUHhq-yembLCV)

## AI Agent Skills

* **Taste Skill** — open-source frontend-design skills for AI coding agents: [website](https://www.tasteskill.dev/) · [GitHub repository](https://github.com/Leonxlnx/taste-skill)
* **Google DeepMind Science Skills** — agent skills for grounded, efficient scientific workflows: [GitHub repository](https://github.com/google-deepmind/science-skills)

## In this section

* [Linear Regression](/statistics-and-bioinformatics/machine-learning/linear-regression.md)
* [Decision Tree](/statistics-and-bioinformatics/machine-learning/decision-tree-cart.md)
* [Random Forest](/statistics-and-bioinformatics/machine-learning/random-forest.md)
* [Logistic Regression](/statistics-and-bioinformatics/machine-learning/logistic-regression.md)
* [K - Nearest Neighbors](/statistics-and-bioinformatics/machine-learning/k-nearest-neighbors.md)
* [Support Vector Machine](/statistics-and-bioinformatics/machine-learning/support-vector-machine-svm.md)
* [Naïve Bayes Classifier](/statistics-and-bioinformatics/machine-learning/naive-bayes-classifier.md)
* [Cluster Analysis](/statistics-and-bioinformatics/machine-learning/cluster-analysis.md)
* [Principal Component Analysis](/statistics-and-bioinformatics/machine-learning/principal-component-analysis-dimensionality-reduction.md)
* [Artificial Neural Networks](/statistics-and-bioinformatics/machine-learning/artificial-neural-networks.md)
* [Apriori Algorithm](/statistics-and-bioinformatics/machine-learning/apriori-algorithm-associated-learning.md)
* [Association Rules](/statistics-and-bioinformatics/machine-learning/association-rules.md)
* [Linear Discriminant Analysis](/statistics-and-bioinformatics/machine-learning/linear-discriminant-analysis.md)
* [Convolutional Neural Networks](/statistics-and-bioinformatics/machine-learning/convolutional-neural-networks.md)
* [Recurrent Neural Networks](/statistics-and-bioinformatics/machine-learning/recurrent-neural-networks.md)