Machine Learning

What is Machine Learning?

Machine learning (ML) is a computer program's ability to learn and adapt to new data and information without human intervention. This machine learning process is also known as a form of artificial intelligence (AI). Machine learning technologies use built-in programs and algorithms to process high quantities of data that provide reliable predictions and identify patterns within current information.

Machine learning helps businesses by:


Benefits of Machine Learning over traditional methods include:

Faster decision making

Machine learning can process data at high speeds and can make rapid decisions based on the previous information collected. For example, machine learning is able to detect anomalies in a company's security environment. It can instantly notify the company to alert them of the issue.

(DataFlair, n.d)

Personalising consumer engagement 

Personalisation has become a popular and critical strategy in today's marketplace. Machine learning platforms can be programmed to analyse user behaviour and suggest additional products based on their search history, purchase history, websites they interact with, and more. Personalisation allows businesses to reach their target audience and boost their products in the market.

(Matillion, 2022)

Increasing efficiency 

Machine learning systems can perform easy and repetitive tasks at high speeds, meaning humans move their focus to more demanding jobs. For example, machine learning technology can perform extensive document searches in a fraction of the time it would take a person to cross-reference one document. This allows companies to reduce the cost of their information retrieval activities while allowing employees to focus on different tasks.

(Matillion, 2022)

Predictions 

Machine learning models are able to analyse and interpret high volumes of data. It's able to predict market trends and customer behaviour. Organisations incorporate machine learning into their data analytics to gain accurate reports that forecast the market's current demands and stay competitive in the market.

(DataFlair, n.d)

Additional Resources

Analysing the effectiveness of an algorithm can be split into 3 categories: