In 2018, we released the first production-ready software for feature learning on relational data and time series. We applied getML's algorithms across different industries and in use-cases with companies like Volkswagen and Carl Zeiss.
By using getML in your project, we can shorten project cycles while delivering more accurate models.Talk to us and find out how we can support you.
Here is a selection of scenarios where we can help.
For pilot or productive use-cases? Where is the relevant data located and what are the data security requirements? Is a private or public cloud available?
Where is the data collected and on what terms? Is it personal data under the defition of the GDPR? Does your data need cleaning, preprocessing, pseudonymization or anonymization?
We can support you with our unique experience in automating feature engineering. What does the data model look like? Have you tried feature learning algorithms or brute force approaches?
What are your requirements with respect to model size? What predictors are you using? Does a hyperparameter optimization or ensembling lead to better results?
Do you need a bulk prediction pipeline or REST API for live predictions? Does your application require regular retraining of your models to adapt them to changing environments?
Feature learning reduces time and costs of data science projects. Here is how we can help you to adopt getML into your ML stack:
Together, we organize an individual tech demo for your data science and data engineering team. It's free of charge!Contact us
Evaluate getML on your predictive analytics challenge with hands-on coding support from the inventors of feature learning.Talk to a solution expert to get started.
For a deep dive into the getML API and relational learning in general, we offer onboarding and training sessions at your pace.