What is Machine Learning
Machine Learning is a branch of Artificial Intelligence that computes its algorithm. It learns from the data, and improves itself according to its experience without human intervention.
Types of Machine Learning
There are four types of machine learning based on different use cases.
Supervised Learning
It is a learning that has both dependent and independent variables where the machine learns from trained data and gives output based on test data. It basically maps input variables to their correct predicted output variable.
Unsupervised Learning
It is a learning that has independent variables without any dependent variables. The machine learns from trained data and gives output based on observing patterns. It identifies hidden patterns, relationships, and clusters about the data points.
Semi-supervised Learning
It is a type of learning that uses both labeled and unlabelled variables. First, it has to predict labeled data and use this labeled data for Supervised learning. This example fits for image classification, where some images have unlabeled data and others have label data. It is useful when the dataset is too expensive to identify the labeled data where it utillize resource intensive.
Reinforcement Learning
It is a type of learning where it interacts with the environment and learns itself based on a reward and penalty basis. If the model correctly identifies the output, they gets the award. Otherwise it will face the penality. It learns from its mistake and retrain itself. It basically improves its performance based on its gain reward. If we feed more data to model, it will give more accurate results and gain more experience.