Let’s be honest to start with. The future is actually not predictable, despite what the title says. Nobody knows what’s coming. Yet we learn our lessons from history and set expectations for our future all the time. We recognize and categorize situations. And when something is not behaving according to our expectations … we get suspicious. Computers don’t learn history like we do. They are not taught to take in lessons from the past as we are. Yet they can help us quite a bit about what will happen by learning from what has happened. With computers we are able to collect lots of data. Historical data that can help us to learn about the future, because it contains patterns and behaviours.
This matter calls for an example: the current energy prices. We know those prices are increasing and we know the energy prices can change widely. Imagine we have a business storing energy (e.g. hydroelectric energy storage). We’d love to know the coming electricity prices to maximize our profit. And what do we discover? That machine learning is perfect to create an algorithm that gives us a prediction of these rates.
The first step in creating this model is to gather the historical data – the training data. This includes historical electricity prices (the target, what we want to estimate) as well as the data that impacts these electricity prices, like the weather forecast at the time (the features). Next, we’ll investigate the impact of the each feature we have on the electricity price. With the relevant features we can train a model that estimates the electricity price based on our features. We now can use this trained model to estimate the electricity prices of the future.
So is the future completely predictable? Of course not. Will you be 100 % certain about a positive outcome according to the algorithm? … Also not. But you will be more prepared, and have a high certainty rate when you use machine learning to learn about the future for your business.
Do you want to know what the future holds for your business? Contact us here.
