The Benefits of Applying Machine Learning

machine learning

Machine learning is a type of artificial intelligence that uses algorithms to analyse large amounts of data to make recommendations and predictions based on their data input. The goal of machine learning is to allow software applications to learn independently with minimal human intervention in order to make decisions, solve problems and predict outcomes by identifying intricate patterns and trends.

Machine learning is used by many of today’s leading companies such as in Google’s self-driving cars, Facebook’s algorithm, Amazon’s online recommendations and Uber’s route predictions. Other popular applications of machine learning technology include malware threat detection, spam filtering, fraud detection, predictive maintenance and business process automation (BPA). Browse here to find out more about how to learn machine learning. This article will explore some of the various benefits of applying machine learning.


Self-Driving Cars

Thanks to machine learning, self-driving cars will no longer be a thing of the future. Algorithms allow vehicles to collect and analyse data on their surroundings through sensors and cameras which are used to form decisions on what actions to perform. Machine learning can be used for tasks such as object detection, prediction of movement and pattern recognition to assist in autonomous decision-making.


High-Risk Environments

Natural disasters can often result in toxic materials entering waterways and polluting drinking water or endangering animals and wildlife. Machine learning can be used by industry regulators to collect data in order to identify high-risk environments which can put lives at risk. Other applications can include fires, chemical spills or nuclear disasters such as Chernobyl, where robots can identify radioactive areas and safely dispose of nuclear waste without the need for exposing humans.




Machine learning can help researchers and clinicians create more precise treatments for patients using predictive analytics to predict how patients will respond to first-line therapies. In 2021, researchers at the Georgia Institute of Technology and Ovarian Cancer Institute used machine learning algorithms to predict how patients would respond to cancer-fighting drugs. Compared to clinical data, the algorithm showed an overall accuracy of 91%.

Machine learning can also help with remote patient monitoring (RPM) which allows patients’ health to be monitored in real-time by collecting information such as vital signs, blood pressure, heart rate and oxygen levels. This allows doctors to monitor chronically ill or elderly patients without the need for in-person visits.



Due to its ability to analyse large amounts of data very quickly, machine learning is being successfully applied in fraud detection to identify suspicious activity, and to verify user identity through its application in biometrics such as facial recognition. Machine learning can process hundreds of thousands of transactions in a fraction of a second and is continually analysing customer behaviour to spot any anomalies, which it can then flag as potentially fraudulent and to be reviewed. This can greatly reduce the risk of cyber-attacks and data breaches in industries such as banking.



Machine learning can help businesses deliver customised content to their customers by creating cross-channel campaigns to find the most optimal version of ads to use and analysing patterns to predict future behaviour.

Machine learning will undoubtedly have greater applications in our everyday lives as time goes on.


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