The AI and machine learning industry is one the world’s most rapidly inflating culture. From helping various technologies advance to generating whole new cultures, AI and machine learning has been playing a vital role.
Data Annotation is one such aspect that has enhanced the field of AL and machine learning. Data annotation is the method of labeling the data obtained in different formats like text, video or images. There companies providing data annotation services for you to enhance your business. For advanced machine learning labeled data sets are needed, so that the machine clearly understand the input patterns with complete ease.
To educate the computer vision based machine learning model, data is required to be minutely annotated using the right tools and techniques. There are multiple kinds of data annotation procedures used to design such data sets for required demands.
Advantages of Data Annotation
Data annotation comprises of text, images and videos to annotate or mark the content of object of interest in the images while checking it to be recognizable by the machines through computer vision.
Data annotation is largely broadening the machine learning algorithm to get equipped with supervised learning methods minutely for correct prediction. However, there are few cons you need to learn about, for understanding it’s relevance in the AI world.
As much as image annotated data is used to train the machine learning model, the accuracy will be higher. The variety of data sets used to train the machine learning algorithm it will learn different types of factors that will help model to utilize its database to give the most suitable results in various scenarios.
Machine learning based trained AI models or automated devices provide a complete variant and unique experience for end-users. Virtual assistant devices or Chatbot guide the users immediately as per their requirements to resolve their queries.
Ensuring the Data Annotation to be Right in the First Go
Even though data annotation can be quite monotonous and time-consuming, it is very essential that everything is executed correctly so that the product can function as expected. Agencies do not wish their in-house to spend time annotating the data since they also are required to work on their primary business functions and having them involved in such low-level tasks is not a right use of their precious hours. There needs to be a strategy planned, that clearly showcases how you manage the data annotation process. You need look after certain key points before you begin the data annotation project to make sure that everything shoots as planned on first go itself.
Understand the Sensitivity of Your Data
If your dataset carries personally identifiable information (PII), then your data can be tagged as sensitive. While PII usually intends to credit card numbers and social security numbers, as far as data annotation is regarded, this also mentions peoples’ faces that can be used to track or spot them. You need to be extremely careful while working on such data
Data that Can Be Automated
Lot of companies are still preferring to hire human data annotations. The machines on the other hand are getting so enhanced that they can perform some tasks independently. This refers to things like data labeling, where they need to recognize the given items in the image such as cars, traffic lights, and pedestrians.
Ways to Motivate Your Data Annotators
Data annotation is an extremely monotonous work and after having annotated hundreds of images, one can easily lose concentration and motivation. To solve this problem, outsourcing providers offer monetary incentives to boost the employees. They can also earn prices for working hard and providing quality work.
A lot of time and money is deployed to redo certain tasks, which is why it is necessary to get everything right the first time. A quality assurance process is mandatory to avoid derailing of the entire project.
Select An Experienced Agency
An experienced data annotation service provider has rigorous security measures assured to prevent any data leaks. They have a sophisticated QA procedure to obtain the job done right in the first time. Therefore it is very crucial for anyone to select an experienced agency with data annotation experts.