The Automated Machine Learning Company
about our technology
MyDataModels automates predictive model generation and deployment.
By automating the entire modelling lifecycle, users can quickly and easily build high accuracy, predictive models.
Deploying models for predictions can now be done with a few mouse-clicks. The platform creates compact models that optimizes the speed and scalability of modeling and can be operated with a standard laptop. Users can generate a complex predictive model in just a few minutes, and major projects that previously took weeks or months to complete can be finished in hours.
Our specific expertise is in Small Data, the most common type of data, and is used to generate compact models in all IoT-enabled industries (where sensors or handheld devices are used), as well as in both the public and private medical and scientific research, where datasets contain tens of thousands variables.
With a one click data-in model-out service, we generate high performance models from Small Data (less than 100 rows) to Big Data (1M+ rows).
Domain-expert users can build predictive models without coding or Machine Learning skills. Data scientists can also leverage the platform to increase their overall work performance and efficiency.
our technology benefits
Automated Machine Learning
Automated Machine Learning automates most of the predictive modelling process, but still requires a high level of coding and Machine Learning skill.
MyDataModels goes much further. Our fully automated Machine Learning SaaS platform provides a range of compelling advantages.
We generate compact models from Small Data (less than 100 rows) to Big Data (1M+ rows). Built to provide a low cost/high value service, MyDataModels combines the latest innovations in predictive solutions with more than a decade of expertise in analytical software development, machine learning and data analytics. The platform is inspired by evolutionary algorithms, as well as a series of unique proprietary algorithms that are fundamentally unlike any other published modern techniques.
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