Validating the AI or ML model is important to make it accurate for right prediction. Evaluating the output given by the running model compared with outputs, if not found satisfying, given with more improved training data. Cogito data annotation team check and evaluate the ML model outputs and validate if its is giving the acceptable results.
Cogito provides training data for AI and ML development, and also offer the ML model validation service to validate the model accuracy level to ensure the right prediction in real-life use. It is working with strong team of image annotation, text annotation and video annotation for different fields like healthcare, retail and automobile etc.
Popular ML Model Validation Techniques:
- Holdout Set Validation Method
- Cross-Validation Method for Models
- Leave-One-Out Cross-Validation
- Random Subsampling Validation
- Bootstrapping ML Validation Method
Many AI and ML engineers develop the model but don’t know how to validate machine learning models, but Cogito has experts who know right ML model validation methods to authorise such machines that can predict itself with right answer and help humans in performing various tasks making their life easier. Cogito is known for unbiased AI model validation service using the accurate training and validation data ensuring the accuracy level at best allowing the ML engineers easily build such models.