Type of Machine Learning

There are primarily three types of machine learning: Supervised, Unsupervised, and Reinforcement Learning.

Supervised Learning

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 just needs to map the inputs to the respective outputs.

Applications-:

    ·     Natural Language Processing

    ·        Image Classification

    ·        Email Spam Detection

    ·        Speech    Recognition

Unsupervised Learning

Unsupervised learning is a type of machine learning that uses unlabeled data to train machines. Unlabeled data doesn’t have a fixed output variable. The model learns from the data, discovers the patterns and features in the data, and returns the output.

 

Applications-:

·        Clustering

·        Data preprocessing

·        Recommendation systems

·        Content recommendation

Reinforcement Learning

Reinforcement Learning trains a machine to take suitable actions and maximize its rewards in a particular situation. It uses an agent and an environment to produce actions and rewards. The agent     has a start and an end state. But, there might be different paths for reaching the end state, like a maze. In this learning technique, there is no predefined target variable.

Applications-:

    ·        Game Playing

    ·        Robotics

    ·        Autonomous Vehicles

    ·        Supply Chain and Inventory Management

    ·        Energy Management