The post Data Labeling: Significance, Tools, Skills and Courses appeared first on Cogitotech ..read more

Through natural language processing (NLP), machines are able to slowly evolve into understanding the way humans converse, emote, understand, respond, analyze and copy human conversations as well as sentiment-driven behaviors. NLP is the key technology behind chatbots, text-to-speech tools, voice recognition, virtual assistants, etc. In the pursuit of training machine learning modules into performing more complex tasks, there is a need for it to be trained with vast volumes of data using data annotation techniques. In case of NLP, the data annotation technique that’s applied is called text anno ..read more

What is Data Annotation? The assignment of attributes, tags or labels to data to assist machine learning algorithms in comprehending and classifying information that requires processing is known as data annotation. It plays a vital role in training artificial intelligence (AI) models and enabling machines in interpreting text, video, image or audio data. It also enables AI to learn and adapt. Hence, high quality AI training data is necessary for training AI models for producing results that are bias-free, representative and successful. Data annotation is not only necessary in model training, b ..read more

Logistics is a very chaotic and time-intensive industry. Artificial intelligence (AI) plays a key role in this industry by assisting the smooth transportation of goods from one location to another. It assists in enhancing, refining, and analysing supply chain operations. Logistics can be seen at play right from the manufacturing floor to the front door. Logistics is also a field that has abundant data along with scope for gathering more data. The creation of new AI solutions for supply chain disruptions involve consumption of a lot of resources. Since shipping and logistics need to be efficien ..read more

The widespread proliferation and usage of artificial intelligence solutions has changed the way industries and enterprises function. The backbone of accurate AI models or solutions that works with enhanced efficiency and accuracy is well-trained training data. If the annotation and labeling of data is of optimum quality and standard, the result will certainly be error-free and efficient AI models. Importance of Training Data for Enterprises Data Annotation is a labour-intensive, cumbersome, and time-taking task which is best left to professionals and the experienced. Cogito endeavors to assis ..read more

The widespread proliferation and usage of artificial intelligence solutions has changed the way industries and enterprises function. The backbone of accurate AI models or solutions that works with enhanced efficiency and accuracy is well-trained training data. If the annotation and labeling of data is of optimum quality and standard, the result will certainly be error-free and efficient AI models. Importance of Training Data for Enterprises Data Annotation is a labour-intensive, cumbersome, and time-taking task which is best left to professionals and the experienced. Cogito endeavors to assis ..read more

A data labeling process is the process of tagging or marking up data in order to identify the outcome that your model is expected to predict. This technique comprises the following steps: Tagging, Annotating, Classifying, Moderating, Transcribing, and Processing the Data. There is often a correlation between the process of labeling data and the process of annotating it. It is common to use data annotation and data labeling in conjunction with each other. By labeling the data, we are able to gain insight into how it is structured, such as its characteristics, traits, or classifications, which c ..read more

Data labeling and/or data annotation has long been a critical component of many machine learning and AI initiatives. In recent years, the demand for accurate and reliable data labeling has risen dramatically as the process becomes increasingly vital to the success of numerous projects. But what is data labeling exactly? Data Labeling 2023 – how will it impact businesses? And what trends should we be aware of now that will shape the future of data labeling? In this blog post, we will explore these questions in an effort to better understand where this technology is headed in the next few years ..read more

Although the world has shifted rapidly towards digitization, some documents and papers still contain some of the most complex information. As public information becomes more abundant, the challenge of making raw, unstructured data machine-readable arises. As a matter of fact, video and images are easier to comprehend than text. As an example, we can take “what’s up.” It is likely the human brain will interpret this phrase as a question, concern, or inquiry about someone. However, a machine may perceive the meaning of the text as it intends to, i.e., what is literally up, such as the fan, the c ..read more

A major step in the development of computer vision systems, AI-based machine learning models, and prediction applications is building well-optimized training data, i.e., the training data that consists of high-quality image annotation and labeling. The AI training data, as a matter of fact, is a principal prerequisite for enabling computer vision systems to recognize, obtain, characterize, and interpret results. Autonomous vehicles, medical imaging, and security & surveillance are some of the AI applications that use computer vision. Image annotation eventually tends to be the most critic ..read more