---
# System prepended metadata

title: 0. Introduction to Machine Learning II
tags: [Machine Learning II]

---

# 0. Introduction to Machine Learning II
###### tags: `Machine Learning II`

:::warning
🤯 Feel stuck with all these technical terms? Take a look at our course on [Machine Learning I](Machine-Learning-I).
:::

This course will be specially focused in **Model developing**.

Modern advanced Machine Learning has three main methods:
* Kernel methods
* Probabilistic Machine Learning (Data models)
* Deep learning (with [Neural Networks](Introduction-to-neural-networks))

This course will specifically cover both **Kernel methods** and **Probabilistc** learning methods.

:::info
**Neural Networks** and **Deep Learning** will be covered by another dedicated course.
:::

## Terminology 

### Novelty detection
It is an [unsupervised learning](Unsupervised-learning) task that studies if a data point belongs to a certain distribution or not.

### Stump classifier
A **stump classifier** is a classifier that uses thresholds to separate instances between the different classes. [Decision Trees](Decision-trees) (DTs) are a recursive application of these kind of classifiers.


