Understanding the basics of Machine Learning


Machine learning is one of the most fascinating applications of artificial intelligence, and it’s becoming increasingly popular in diverse fields. It’s a subfield of AI that provides systems with the ability to learn and improve performance from experience without being explicitly programmed.

What is Machine Learning?

Machine learning is the study of computer algorithms that learn from data and observations and make predictions or decisions without being explicitly programmed. It involves applying statistical methods to large datasets to infer relationships between different variables.

Why is it important?

Machine learning has become essential because it helps to analyze and extract insights from big data, which can be used to make critical business decisions. It’s used in diverse fields like health care, finance, retail, and more.

Types of Machine Learning

The two most popular types of Machine Learning are:
  • Supervised Learning: It involves learning from labeled data to make predictions or decisions. For instance, predicting the price of a house by analyzing its different features.
  • Unsupervised Learning: It involves learning from unlabeled data to find hidden patterns or relationships. For instance, clustering customers based on their spending patterns.


Machine learning is an exciting field that presents incredible opportunities for individuals and businesses. By using complex algorithms and big data, machine learning can provide valuable insights into any business problem.