The full cycle of building production machine learning systems: developing systems for collecting initial data (.NET, .NET Core, Python), developing ETL systems, developing systems for feature generation and data labeling, developing machine learning models, developing integrations for delivering machine learning results to end systems, development of dashboards for building analytics of systems operation. Expertise third party machine learning systems, processes and logic behind source code.
Having expertise covering different Data Science aspects, our cross functional data science team able to deliver ML as a complete product. From statistical analysis and feature engineering to underlying infrastructure, data integration code and UI everything could be bundled into single viable product with agreed deliverables.
Technologies
- Python
- R
- Numpy
- Pandas
- XGBoost
- SVM
- LSTM
- Azure ML
- IBM Watsons
- Google AI