Data Annotation is the process of attaching labels to datasets that are used for training machines. About 80% of Artificial Intelligence project development time is spent on data preparation. The success of any AI or Machine Learning project is directly proportional to the quality of the annotated data fed to the algorithms for training them. Even the slightest of errors can prove disastrous to humankind especially when you trust machines with your life.

Data Annotation for Supervised & Unsupervised ML Algorithms

Data Annotation plays a crucial role in the training of the machine learning algorithms more so in the case of supervised ML projects. Annotated data helps the machines to understand its surroundings better and identify the objects in its vicinity.

When it comes to unsupervised ML project, you would need annotated data sooner or later to improve the performance of your ML algorithms. Human data annotation can play a key role to increase the accuracy rate of an unsupervised ML algorithm that learns on its own by connecting the dots. In such cases, human annotators can manually review each image to determine if the quality of the annotated image is good enough for the algorithms to learn or not.

Are Open-Sourced Datasets a Good Choice for AI/ML projects?

Even though there are open-sourced annotated data available, not the best option to consider. As per Mckinsey, about ¾ of AI projects would need monthly data refresh while 1/3^rd of them need a weekly data refresh. As the datasets need to be refreshed every week, using the publicly available datasets may not be good for your AI/ML projects.

Trust Data Labeler with All Your Human Data Annotations Needs

Data Labeler specializes in building comprehensive datasets that are perfect for training your ML models. Even though Data Annotation is a very significant part of your AI/ML undertaking, you don’t have to worry about spending time annotating data yourself. We will do the heavy weight-lifting part while you focus on optimizing your AI/ML models to perfection. Write to us at sales@datalabeler.com for customized training datasets for your AI/ML projects.

Can you build Machine Learning models without data? The answer to that question is an obvious NO. Whether you are creating supervised or unsupervised algorithms, annotated data is the key to successful #MachineLearning projects.

And about 80% of Artificial Intelligence project development time is spent on data preparation of which #dataannotation is an indispensable stage.

Read the blog to find out how valuable is #AnnotatedData and the role it plays in the development of highly-efficient #MLModels

what crucial role does data annotation play in the development of 

Is it possible to build Machine Learning projects without data? Whether supervised or unsupervised machine learning development require data annotation