AI
sprint cycle
The Plank AI lab consists of dedicated teams of data scientists, data engineers and mlops engineers that work with innovative technology companies on their most difficult challenges.
Business problem formulation
- Interviewing stakeholders and documenting research
- Objective formulation of business problem along with key metrics
- Defining successful outcome concretely
Data cleaning and data pipeline engineering
- Consolidation of input data sources and schema
- Data analysis to assess missing data, mistyped data
- Creation of consolidated / clean schema of data
- Creating data pipelines
- Deploying data pipeline and batch jobs to populate data lake
Data Science & Model training
- Creating training, test, validation datasets
- Formulating model experiments and tracking model performance
- Tuning of model hyper-parameters
- Optimization of model performance
ML model coding and deployment
- Implementation of prediction API endpoints
- Creation and deployment of model microservices
- Tracking of model performance
- Setup regular model retraining
- Model versioning
Model AB testing
- Integration with data warehouse and analytics services for continuous model performance evaluation
- Defining model variants and AB testing experiments
- Mapping model performance to key business metrics
Engineers we’ve worked with
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