Why Machine Learning Model Validation in Important for AI Models?

by Roger Brown Manager

Validating the machine learning model outputs are important to ensure its accuracy. Basically, when machine learning model is trained, (visual perception model), there are huge amount of training data sets are used and the main motive of checking and validating the model validation provides an opportunity to machine learning engineers to improve the data quality and quantity. 

Why ML Model Validation is Important?   

Actually, without checking and validating the model it is not right to rely on its prediction. And in sensitive areas like healthcare and self-driving cars, any kind of mistake in object detection can leads to major fatalities due to wrong decision taken by the machine in the real-life predictions. And validating the ML model at training and development stage helps to make the model make the right predictions.

How Machine Learning Model is Validated?

How To validate machine learning model, there are certain techniques used in AI world. But using the right validation model is the important to make there is no business in validating the machine learning model. And there are two types of machine learning model validation process – human backed validation and automated validation using the another AI model for such validation.    

Automated vs Human ML Model Validation: Which one is Better?

Automated ML validation can do the process faster but there could be compromise with the accuracy. So, human back manual ML model validation can do this process with more accuracy. And if any deviation found in the predictions, it is corrected with right training data sets.  

Why ML Model Validation is Beneficial?

Compare to automated validation, in human backed ML validation process the prediction results are is evaluated by a dedicated team while ensuring the quality. And this kind of approach helps, to improve the accuracy of model for precise predictions, especially for sensitive AI models. And best of human backed annotation is they do this job in unbiased manner for accurate validation.

Cogito provides the training data sets for machine learning model validation. It can validate the machine learning model with high level of accuracy. It is working with well-trained and highly skilled image annotation team to check validate the different types of models at affordable pricing. For visual perception model, annotation QA services is offered by Cogito making them work properly in various scenarios for different fields like healthcare, retail, automotive and agriculture etc.     


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About Roger Brown Innovator   Manager

21 connections, 1 recommendations, 89 honor points.
Joined APSense since, January 29th, 2018, From New York, United States.

Created on Jun 1st 2020 05:02. Viewed 159 times.


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