what are the types of Machine Learning
Supervised learning is the most common type of machine learning.
In supervised learning, algorithms are trained on a labeled dataset, meaning the data is tagged with correct answers.
The algorithm then learns to map the inputs to the outputs.
The algorithm will be given a dataset of digit images, each labeled with the correct digit (0, 1, 2, etc.)
The algorithm will then learn to identify features of the digits and use those features to classify new images of digits.
Unsupervised learning is a type of machine learning where the algorithm is not given any labeled data.
Instead, algorithms are tasked with finding patterns in the data itself.
Semi-supervised learning is a type of machine learning that falls somewhere between supervised learning and unsupervised learning.
In semi-supervised learning, the algorithm is given a dataset that is partially labeled
This means that some data is tagged with correct answers, but some data is not labeled.
Reinforcement learning is a type of machine learning where an algorithm learns by interacting with its environment.
The algorithm is given a set of goals, and it learns by trial and error how to achieve those goals.
For example, a reinforcement learning algorithm can be used to train a robot to play a game.
The algorithm will be given the goal of winning the game, and it will learn by playing the game repeatedly and trying different action