What is Machine Learning

Machine learning describes the use and development of computerised systems that can adapt without following explicit instructions or code. These machines typically learn from algorithms and user data to conclude data patterns and can be combined with deep learning and artificial intelligence to create automated solutions to data management and distribution.

Machine learning was first developed in 1952 by computer scientist Arthur Samuel, who created the first machine learning program in which a computer was taught to play checkers by analysing its human opponents' moves and being able to use them again at a later time. This concept has been expanded on over time with the capabilities of machine learning vastly increasing, especially after the introduction of the internet in 1983.

Machine Learning vs Artificial Intelligence

Machine learning has been used to power the development of artificial intelligence however, during the 70s and 80s there was a separation between the two fields. Where machine learning used algorithms and user data to develop its database, artificial intelligence opted for a more contemporary approach by using knowledge and logic. Machine learning allows machines to learn from new data for a single specific purpose without the use of explicit programming, whereas artificial intelligence captures the larger concept of attempting to mimic human thinking and problem-solving.

Machine Learning Today

Today machine learning makes up a significant portion of our online experience, even if we aren’t aware of it. Every product recommendation, social media post, or video has been specifically curated by a machine learning algorithm that uses data based on your browsing habits, age, and location to perfectly curate advertisements and content it thinks you will enjoy.

Machine Learning in Cybersecurity

Within cybersecurity, machine learning has slightly more practical uses. Organisations can harness the power of machine learning to vastly improve their cybersecurity with minimal effort. Machine learning allows the security programme, be it DDoS protection, malware scanning, or user authentication to make educated decisions based on previous activity and patterns and provide custom alerts depending on the threat detected – allowing cyber security teams to act promptly on any discrepancy.