Why Human Annotated Datasets is Important for Machine Learning?
By Rayan Potter | 07 June, 2019 in Annotation Services | 3 mins read
Developing an AI model through machine learning is not possible without huge volume of data like training data, testing data and validation dataset that requires at various stage of development. Actually, machines learning models use an algorithm to learn the patterns in the input through such data sets that are fed into the models.
To develop a right and fully functional model you need to have the right amount and quality of data sets that should be organized and structured in the right formats covering all types of variations learn to your ML model and give the right prediction in real-world scenario.
However, the quality structured data can be gathered through human-annotated data that is also very much important for machine learning model development. In such fields humans can do better in terms of subjectivity, managing, understanding intent and confronting with uncertainty.
And while training a computer vision or pattern recognition solution for machines, humans are necessary to identify and annotate images data like outlining the various objects like traffic signs, tress and other objects making it recognizable for machines.
And most of the AI-based applications needs models to be consistently trained to make them adjustable as per the changing conditions in different scenarios. Right here we will discuss why human annotated datasets is important for AI-based machine learning with use cases.
Improved Search Relevance for Different Markets
Online search engines needs huge amount of data sets to improve the quality of its search results which should be presented as per the culture and market trend globally. Human annotated data sets at Anolytics helps to achieve the AI companies goal and develop a successful machine learning model for best response and predictions.
Human annotated data sets are labeled with right technique and video annotation tools to make it recognizable to computer visions or machines. Different types of data sets annotated by humans for different scenarios help model to learn with variety of data that can give the more precise prediction as per the behavior and patterns learned during the model training.
Accuracy and More Reliability with Scalable Solution
The annotated data for machine learning needs to be highly accurate, so that model can learn the true scenarios and predict accordingly. Humans not only annotated carefully but also check the annotations using the suitable tools and techniques. Humans can annotate the data for different needs as per the model development needs while working with scalable solution to expand their workstations or annotators to provide the scalable solution to every client.
The job done automatically have lots of inaccuracies especially in terms of quality that humans can give at better rates mainly when there is irregular shapes comes for annotations. In such situations, humans can annotated the image data per the object dimension or shape. The accuracy is best and reliability is also higher due to manual checking and validation by humans that also validate such data at the time of training.
Humans Can be the best One-stop Annotation Solutions
A dedicated software or automated tool can have limited types of data annotation functions that annotated particular type images or objects in shapes. While on the other hand, humans can annotate different shapes and size of objects available in various formats. They can do this job with full customization for flexible annotation service at affordable cost.
And while working on different types of image & data annotation projects, humans becomes experienced enough to annotate pictures of any size and formats. These experts provide the final review and corrections and help models learn with corrected data sets and give the best results. Anolytics is one of the emerging companies providing human-annotated datasets for machine learning and deep learning for different sectors and sub-fields.
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