What is a predictive model?
Artificial Intelligence (AI) is among the most discussed topics of the last 10 years. As the volume of collected data increases dramatically, technics such as Machine Learning, Deep Learning or Predictive Modeling become a part of our everyday concerns.
Let’s take a look at Predictive Modeling. It can be defined as the process that uses a historical dataset to build a mathematical solution with the purpose to predict outcomes from new data. Basically, it means that you use old data with verified results to build a mathematical model. This model will then be used to calculate predictions, i.e. the information you want to predict out of new datasets.
Examples of predictive modeling use cases
These days, predictive modeling is used to predict anything, from soccer games results (France wins in the end) to the success of the latest Hollywood blockbuster (superheroes flicks win in the end).
But, on a more down-to-earth approach, professionals with small volumes of data can also need to build predictive models, no matter the area they’re working in:
- As doctors and surgeons collect increasingly more data from their patients, they build data sets with various factors and outcomes. This data can then be used to build predictive models and identify as early as possible potential risks of sicknesses, providing upcoming patients with the right treatment to avoid it. Read More.
- In industrial environments, maintenance is key to keep equipment up and running and avoid failures. As more data is collected from machines, production managers can build predictive models to anticipate upcoming failures, adapt maintenance planning and guarantee the continuity of production. Read More.
- For the sales & marketing departments, it is vital to limit the number of customers that go and see what the competition does. To that effect, they can build predictive models out of their customer data to efficiently predict who will leave them and engage into corrective actions. Read More.
Of course, these are not the only professional areas where domain experts can benefit from it. If you have some Small Data sets and you want to use them to predict more efficiently future results, why not try it by yourself?
TADA by MyDataModels lets you create your own models, in a few clicks, without any code or data science knowledge needed.