Have you ever asked yourself: “What are the different machine learning algorithms, and in what industries are they applied?” The University Herald has answered this question for us, listing seven machine learning algorithms worth knowing about and why they are so important.

The industries mentioned reach from medicine to finance and cover many of the industries that AI Business are working closely with, hence why it would be interesting to look at how these different industries make use of machine learning algorithms, and where they differ. It is also a very good insight to what artificial intelligence can do for various industries, and where its potential is.

The purpose of a machine learning algorithm is to identify incorrect or correct data that the system is provided with, in a specific structured way. First, the machine is provided with a “teaching set” of data, which is later used to answer a question University of Herald explains. This is to ensure that the machine is given the correct instructions.

Secondly, the machine is asked more and more questions, and with this new information adding to the algorithm, it makes it smarter and better and performing the given task over time. Hence why you could say the machine is “learning” by doing.

Financial Trading:

In the financial trading industry, machine learning algorithms are often used for the purpose of predicting the stock market ahead of time, as is information that is in high demand. Hence why many trading companies are creating their own systems dedicated to predict and execute trade at a high pace. The University Herald explains that most of these are based on probabilities, and even in situations where the probability is low but executed at high volumes, it still has potential to generate a lot of profit. The result is that financial machine algorithms now are becoming more and more sophisticated at predicting these probabilities.

Data Security:

Malware, described as a term referring to a variety of forms of hostile or intrusive software, such as computer viruses, Trojan horses etc., that can take the form of executable codes, scripts, etc., is now becoming a huge threat to data security. The intelligence company Deep Instinct explains that despite new malwares being developed it appears that each of them include the same code as its previous version, with only 2 to 10 percent change in every iteration. This is where machine learning algorithms can detect these anomalies as well as predicting security breaches by analysing these patterns.


Machine learning algorithms have the potential of significantly improving the medicine industry, by detecting risk factors for diseases prior to what a human doctor would do. University Herald refers to a study where a computer assisted device were used to detect breast cancer risk, where the machine was able to identify 52 percent of women by analysing mammography scans of the participants. There have also been incidents where algorithms have detected diabetes prior to identifying eight variables.

Fraud Detection:

Companies such as PayPal use machine algorithms to prevent fraud and money laundering in their services. It is conducted by algorithms spotting and detecting fraudulent or legitimate transaction by analysing the transactions.

Online Search:

Online Search-portals such as Google uses algorithms to tailor the search for its users. If you ever wondered how Google can guess words prior to you even typing them, that is through the use of algorithms. The Google algorithm collets, analyses and then detects user preferences. Hence why it can predict what your next search move will be.

Personal Security:

Machine learning can also add valuable assistance to security, such as airports, security in buildings or public places and events. It allows to eliminate any potential risk or false alarms in the most efficient way, which can reduce any potential threats significantly.


Algorithms are particularly essential and helpful in marketing-industries because it provides each company with information and knowledge about who their customers are, and their needs. It can analyse anything from buyer-habits and helping businesses customise their customer service to ensure that the users feel even more valued. This can again increase the customer satisfaction and the company’s reputation.

Photo Credit: Google

This article was originally posted at: http://www.universityherald.com/articles/44353/20161015/machine-learning-algorithms.htm

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