Machine-Learning-Model-Validation

Top Machine Learning Model Validation Techniques

Machine Learning, Technology , , , , , , 0 Comments

Machine learning model validation service to check and validate the accuracy of model prediction. Cogito offers ML validation services for all types of machine learning models developed on AI-based technology. It has highly skilled and experienced machine learning engineers to validate the ML models and make sure the predictions should be accurate. It is doing this job manually by team of annotators using the various model validation methods.

model validation services

ML Validation Techniques Used by Cogito:

  • ML Model Validation by Humans
  • Holdout Set Validation Method
  • Cross-Validation Method for Models
  • Leave-One-Out Cross-Validation
  • Random Subsampling Validation
  • Teach and Test Method
  • Bootstrapping ML Validation Method
  • Running AI Model Simulations
  • Overriding Mechanism Method

All types of model validation techniques to ensure the each model can work precisely and give the best results. These ML engineers follow the best validation process to authenticate the machine learning models developed through deep learning algorithms. It is providing the unbiased AI Model Validation Services for machine learning with highest accuracy at affordable pricing helping AI developers to build an accurate model for different fields.

Source

Comments

comments

Published by

Cogito

Cogito offers a complete data collection and processing service for training data as a services for AI and Machine learning based services. It is providing wide range of services like Visual Search, Image Annotation, Machine Learning, Sentiment Analysis, Data Collection, Data Classification, Search Relevance, healthcare training data, contact center services, Content Moderation, Audio Transcription, Video Transcription and OCR Transcription services with high quality and accuracy.

Leave a Reply

Your email address will not be published. Required fields are marked *