Machine learning is a type of artificial intelligence (AI) that gives our computers the ability to learn without being manually programmed. Machine learning focusses on developing computer programmes to allow them to evolve and adapt when exposed to new data.
Evolution of Machine Learning
Like everything in the world of technology, machine learning has come a long way over recent years. It was born from the simple idea that computers don’t need to be explicitly programmed in order to carry out every new task; instead researchers wanted to see if these machines could learn from new data.
Although it’s not a new technology, machine learning is definitely regaining momentum and coming to prominence. Here are just a few examples of machine learning that you may have recently seen publicised:
- Online recommendation offers. This form of remarketing relies on technology to build ‘smart lists’ in order to define consumer profiles.
- Fraud detection
- Self-driving vehicles
Why is it so important?
There’s no doubt that the resurgence of interest in machine learning is due to developments within the technology environment. We now have more data (and varieties of that data), cheaper computer processing and more powerful, affordable data storage.
These factors combined now make it easy to produce systems that can analyse more data quickly and more effectively. This provides us with faster results even when looking at huge amounts of data; and is crucial when it comes to identifying opportunities and minimizing risks.
Who’s using machine learning?
These days large amounts of data are present in many industries; and businesses are starting to recognise machine learning as an effective way of dealing with and analysing this data.
Using this companies are able to gain an insight into specific markets and identify opportunities in real-time.
Machine learning is rapidly growing within the health care industry; this is in no small part down to the plethora of wearable devices that can now use data to monitor our health.
Marketing and sales:
As mentioned previously, machine learning plays a huge role when it comes to remarketing. This works by search engines, predominantly Google, analysing your purchase history and then showing you other items you may be interested in.
It’s within many government bodies’ interests to make sure that they analyse their data as effectively and efficiently as possible. It’s possible for the utilities agency to see opportunities for savings by using data collected from sensors. For example, they can see if nobody uses a particular road between specific times; so in that case there’s no need for street lamps to be active.
There are two main reasons why businesses in the financial industry are taking advantage of machine learning. Firstly to help provide important insights such as spend patterns; and secondly to prevent fraud.
For an industry whose stock-in-trade is to make routes more efficient and predict potential problems, being able to identify patterns and trends is crucial. It’s a key part of any delivery company or transportation agency.