MACHINE LEARNING

Introdction to Machine Learning

Machine Learning is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and models that allow computers to learn and make predictions or decisions without being explicitly programmed. 

It involves the study of algorithms and statistical models that enable computers to learn patterns from data and make accurate predictions or take actions based on that learning.

The main idea behind Machine Learning is to enable computers to learn from examples or past experiences and use that knowledge to make informed decisions or predictions on new, unseen data. 

Instead of being explicitly programmed with a set of rules or instructions, machine learning algorithms learn patterns and relationships from data through a process called training. 

This training involves providing the algorithm with a dataset containing input data (features) and corresponding desired outputs or labels. The algorithm then learns from this labeled data to generalize and make predictions or decisions on new, unseen data.

There are various types of machine learning algorithms, each suited for different types of problems and data. Some common types include:

In addition to these main types, there are other learning paradigms that incorporate elements from multiple types or have specialized characteristics: