Types Of Machine Learning algorithms

1. supervised learning algorithms: these algorithms learn from labeled training data, where the output is known. examples include linear regression, logistic regression, and support vector machines. 

2. unsupervised learning algorithms: these algorithms are used when there is no labeled output. examples include clustering and dimensionality reduction. 

3. reinforcement learning algorithms: these algorithms interact with a dynamic environment, with each interaction yielding a reward or penalty. examples include q-learning and deep q-learning.

4. generative adversarial networks: these algorithms use two neural networks to create and enhance data. examples include deep convolutional gans and stylegans.