Continuous Learning
Continuously improve artificial intelligence models with custom learning lifecycles.
Supervised and unsupervised loops to update, adapt and improve model performance over time as they are exposed to new data or changing conditions.
- Development of the continuous learning strategy
- Identify relevant data sources for model improvement
- Determine accuracy and relevance baseline
- Implement supervised/unsupervised learning loops
- Stakeholders satisfaction evaluation and pain point assessment
- Collaborative model design
- Continuously update and improve models based on new data and changing conditions
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Our Artificial Intelligence Tasks
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