What's included

• Data Collection and Preparation

  - Collect, clean, and preprocess data required for model training - Implement data augmentation and annotation techniques to ensure accurate labeling - Establish data pipelines and ensure data quality and consistency

• AI Model Development and Evaluation

  - Develop custom AI models tailored to client needs - Design and implement model training processes to prevent overfitting and improve robustness - Evaluate and report model performance using appropriate metrics and benchmarks

• Deployment and Integration

  - Deploy trained models into production environments - Integrate ML and CV models with existing systems and APIs - Implement observability mechanisms to track model performance