# Machine Learning (ML) *Machine learning is the field of knowledge upon which modern artificial intelligence systems are built.* As the name might have hinted, machine learning is, at its core, the construction of methods in which computers can recursively educate and advance their comprehension of certain subjects. Based on neural networks that replicate human thought processes, ML is an aggregation of complex algorithms that can distill abstract principles into tangible mathematical formulas. Concepts such as linear regression, clustering, and random forest structuring are examples of decision-making techniques that are utilized to make learning possible. Depending on who you ask, there are three general classes of learning models: Supervised, Unsupervised, and semi-supervised, each containing a multitude of hybrid alternative sub-models (reinforcement, temporal, etc.) within them. ChainGPT’s AI leverages all of the leading open standards in machine learning to optimize its model’s aptitude to evolve alongside ingesting new data. [**Disclaimer**](/misc/legal-docs/disclaimer.md) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.chaingpt.org/overview/learn-the-concepts/machine-learning-ml.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.