What's included

• Data Collection and Preparation

  1/ Assistance in collecting, cleaning, and preprocessing the data required 2/ Support on data augmentation, annotation techniques, ensuring that datasets are accurately labeled and ready for model training 3/ Establish data pipelines and ensure data quality and consistency

• AI Model Development and Evaluation

  1/ Development of custom models tailored to the client's unique needs implementing best practices in model architecture design, hyper-parameter tuning and regularization to optimize model performance and generalization 2/ Design of training processes of AI models, ensuring that they learn from the provided data effectively to prevent overfitting and improve model robustness 3/ Model evaluation and reporting using appropriate metrics and benchmarks, validating the models' performance against real-world data and business requirements

• Deployment and Integration

  1/ Collaboration with client's technical team to deploy the trained models into production environments seamlessly 2/ Guidance on integrating the ML and CV models with existing systems and APIs ensuring smooth operation and scalability 3/ Implementation of observability mechanisms to track model performance