What is Machine Learning - A Brief Introduction – Buddhilive Developers

What is Machine Learning - A Brief Introduction



Machine Learning has become popular these days. But what is machine learning? Machine Learning is a subset of Artificial Intelligence. (Read the difference between Machine Learning and Artificial Intelligence). Machine Learning is set of computer algorithms that helps to make predictions without being explicitly programmed. What does that mean?

In traditional programming, we enter rules and data to the computer and get answers. Programmers should figure out the rules to get the expected answers. In machine learning, we feed data and answers to the computer and we let computer to figure out the rules. This process is called training. After the training, the machine learning algorithms build a mathematical model based on the training data we provided. This model can be used to predict or make decisions.

There are three main types of machine learning methods;
  1. Supervised Learning
  2. Unsupervised Learning
  3. Reinforcement Learning

Supervised Learning

In Supervised Learning, we provide training data with their desired output (i.e. labels). So we train the model using that data until it predict the answers accurately. This is the most common method used. This is used for image recognition, object detection, face detection, voice recognition etc.

Unsupervised Learning

In unsupervised learning, we provide training data only. The machine learning algorithms try to find clusters of data based on their similar features. In supervised learning we use structured data, but in unsupervised learning we don't use structured data. It is up to the machine learning algorithm to find hidden structures in the data.

Reinforcement Learning

In reinforcement learning, we let the computer to interact with a specific environment and perform actions. When the computer perform correct action, we reward it, if not we punish it. Well, the goal of the machine learning algorithm is to collect maximum rewards. This is like trial and error training. This approach is commonly used in game development. AI agents like AlphaGo which defeated world best Go players are trained using reinforcement learning.

This is a very brief introduction to machine learning. We'll learn how to use these methods in the future.
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