Break the Limit of Your Data Science Team!
The number of models that a business can use is almost limitless:
(The number of products) x (number of segments/customers) x (number of campaigns) = many models your business may need.
On the other hand, there is a limit to the number of models a data scientist team can build, validate, and maintain.
To break this limit we need both a new way of working and a new tool. We need a system that will assist and automate the day-to-day work or your data scientist team.
This tool is a model factory and with it a very small team of data scientists can easily build, deploy and maintain multiple models.
How does it work?
In the traditional world of data science, to build a model estimating a given segment’s propensity of buying a given product would be created bya data scientist through the following steps:
- build the training dataset by combining the desired target with the predictors;
- spend a lot of time cleaning the data;
- create new features;
- test algorithms (depending on how much time they have) with few or several hyper parameters;
- select the best one;
- create a scoring script to deploy the model;
- Once the model is in production, track the model perform to be sure that it is still performing well.
This whole process can take between days or weeks for just one model! and must be repeated as many times as the number of models that needs to be built.
With a model factory, instead of building one model at the time, the data scientist builds a “model recipe” that can be applied to create multiple new models. The data scientist decides which features should be tested in a model, how the feature building should be done, what models should be tested, and how the best model should be chosen.
Once the model recipe is finished and uploaded into the model factory it can be automated to create as many models needed, be it 10, 100, or 1000. The same model recipe can also be used to retrain existing models with new data automatically (by following the same recipe) to be sure the each is performing at its optimal level all the time.
This paradigm shift in the work of the data scientist is simple but powerful. Instead of building models one by one, they create algorithms used to build countless models automatically. The power of automation will multiply the productivity of your data science team.
Accéder's Modeling Factory Service
Accéder’s data team and technology partners has created a core Model Factory that allows us to produce multiple data models for our clients in a shorter period of time, while costing less than traditional methods. Our Software is tailored to the needs and models demanded by our clients.
We provide this service by adjusting the core to clients’ models. After producing a first series of models and going through a validation process, we keep producing models until we reach a high prediction level, that either matches or is superior to those used by the clients. Once our Model Factory is producing the models we want, we can generate models in a matter of days instead of weeks!
We can also develop client modules with computer interfaces to provide clients with direct and remote access to our Model Factory. After basic training, the client’s data scientists can use our Model Factory to generate their own models production. A two year license agreement is required to get the models created and receive training.