What is Machine Learning?
Machine learning is a branch of artificial intelligence. Machine learning uses algorithms to train computer systems and imitate the way that humans learn. The process of teaching a computer how to build associations through inputting data is referred to as training.
Training Models
There are four main training models for machine learning. Supervised, Unsupervised, Semi-supervised and Reinforcement training.
Supervised Machine Learning: In supervised machine learning the system is fed labeled datasets (input = output) into an algorithm so that is can accurately learn to predict future outcomes.
Unsupervised Machine Learning: In unsupervised machine learning the system is fed an unlabeled dataset (input = ?) and the algorithm is left to discover patterns without human intervention.
Semi-Supervised Machine Learning: In semi-supervised machine learning the system is fed a small labeled dataset, as it is in supervised, and a larger unlabeled dataset. This allows for some level of control like in supervised training without the need to create a large labeled dataset.
Reinforcement Machine Learning: In reinforcement machine learning the system is forced to iterate through a problem multiple times and learns based on trial and error.
Machine Learning in JS
JavaScript has multiple libraries that allow for building machine learning algorithms. Some of these include Brain.js, Math.js, ml5.js and TensorFlow. Following is an example of reinforcement machine learning called neuroevolution.
Top comments (1)
very precise and to the point. Easy to understand even for dummies