# Machine Learning Models Algorithms

There are three types:

### Supervised Learning

eg. Regression, [Decision Tree](https://www.analyticsvidhya.com/blog/2015/01/decision-tree-simplified/), [Random Forest](https://www.analyticsvidhya.com/blog/2014/06/introduction-random-forest-simplified/), KNN, Logistic Regression

### Unsupervised Learning

eg. Apriori algorithm, K-means

### Reinforcement Learning

eg. Markov Decision Process

### List of Common Machine Learning Algorithms

1. Linear Regression
2. Logistic Regression
3. Decision Tree
4. SVM
5. Naive Bayes
6. kNN
7. K-Means
8. Random Forest
9. Dimensionality Reduction Algorithms
10. Gradient Boosting algorithms
    1. GBM
    2. XGBoost
    3. LightGBM
    4. CatBoost


---

# 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://lauradang.gitbook.io/notes/machine-learning/algorithms/machine-learning-models-algorithms.md?ask=<question>
```

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.
