What is Machine Learning?

Machine learning (ML) is a type of artificial intelligence (AI) that allows computers to learn and improve from data without being explicitly programmed:

How it works

ML uses algorithms to analyze data, identify patterns, and make predictions. The more data a machine learning system is trained on, the better it gets at making predictions.

Applications

ML is used in many areas, including healthcare, entertainment, shopping carts, and homes. For example, a financial organization can use ML to classify transactions as fraudulent or genuine.

Benefits

ML is a good choice when data is always changing, or when coding a solution would be difficult. It can also help companies make data-driven decisions to streamline their operations.

ML is a key tool for data scientists, who use it to uncover patterns and make predictions in data.

Some prerequisites for learning machine learning include:

Math

Machine learning uses intermediate to advanced math concepts, like linear algebra, probability, statistics, calculus, and trigonometry. These skills are used to create algorithms, run regression analysis, build data models, and interpret data. 

Programming languages

Python is a common programming language used in machine learning. 

Statistics

Understanding the theoretical foundations of statistics helps you understand the limitations of machine learning models. 

Probability

Probability helps predict the likelihood of occurrences, which is a foundation for machine learning.