Machine learning is an application of artificial intelligence that learns from large amounts of data to solve specific problems. It uses computer algorithms to automatically improve efficiency through experience.
There are three main types of machine learning: supervised, unsupervised, and reinforcement learning.
supervised learning
overview
Supervised learning is a type of machine learning that uses labeled data to train machine learning models. In labeled data, the output is already known. The model only needs to map inputs to corresponding outputs.
For example, an example of supervised learning is training a system to recognize images of animals.
Attached below is the model we trained to recognize cat pictures.
algorithm
Some of the most commonly used supervised learning algorithms include:
- linear regression
- logistic regression
- Support Vector Machines
- K-Nearest Neighbors
- decision tree
- random forest
- Naive Bayes
working principle
Supervised learning algorithms map labeled inputs to known outputs, which means our implementation already knows the target variable.
Now, let's focus on the training process of supervised learning methods.
supervised learning