Perhaps, you all are very familiar with some terms such as Big Data, Machine Learning, Deep Learning,… In these fields, data is considered one of the most important things. Nowadays, data is becoming more and more diverse. Therefore, the computer will have difficulty recognizing the raw data. For that, data labeling is an important step to train machine feature recognition. Let’s find out some information about “Data Labeling” with TagOn right now.
What is data labeling?
What is data labeling
Nowadays, many practical machine learning models make use of supervised learning, which uses an algorithm to map an input to an output. To let supervised learning work, a labeled set of data is necessary for the model to learn to make the right decisions. Data labeling normally begins by asking people to make judgments about some unlabeled data. For instance, people labeling may be required to tag “the photo contains a car” for all the images in a dataset. The tagging can be as rough as or as detailed as identifying the specific pixels in the image involving the car. The machine learning model utilizes labels provided by people to learn the underlying patterns in a “model training” process. The result is a trained model for the new data to be predicted.
In machine learning, the data labeling used as the objective criteria to train and assess a certain model is usually called “ground truth”. How accurate your trained model is will depend on how accurate your ground truth is. Therefore, taking time and resources to make sure the highly accurate data labeling is important.
The popular data labeling
Type of data labeling – Computer Vision
Type of data labeling – Computer Vision
When creating a computer vision system, people first need to label images, key points or pixels. Otherwise, we can make a border fully enclosing a digital image, called a “bounding box”, to create the training dataset. For instance, we can classify images by quality type or content, or we can segment an image at the level of the pixel. Then we can use the training data to create a computer vision model that can be utilized to automatically detect the location of objects, categorize images, segment an image, or identify key points in an image.
Type of data labeling – Natural Language Processing
Natural language processing first needs us to manually identify essential sections of text or tag the text with unique labels to create your training dataset. For instance, you would like to identify the intent or sentiment of a text blurb, identify speeches, classify proper nouns, and identify text in images, PDFs, etc. To do this thing, you may draw bounding boxes around text and then transcribe the text in the training dataset manually. The models of natural language processing are utilized for sentiment analysis, optical character recognition, and entity name recognition.
Type of data labeling – Audio Processing
Audio processing converts all types of sounds. All the speech, building sounds (breaking glass, scans, or alarms), and wildlife noises (barks, whistles, or chirps) will be converted into a structured format to be used in machine learning. Audio processing usually asks us to first transcribe audio into written text manually. Therefore, we can explore deeper information about the audio by labeling and classifying the audio. This classified audio will become our training dataset.
The Data Labeling services of TagOn
Tagon’s service – Data Collection
First, TagOn owns many different kinds of data for scaling up. This helps capitalize TagOn’s diversified crowd to distribute large-scale data collection of many kinds: text, audio, image & video, and scale your project in both quantity and variety.
Second, TagOn has automated data verification tools to make sure the quality of data. With the verification tools and system-embed quality for all kinds of data to deal with data quality assurance, TagOn can ensure r any-volume data collection greatly.
Finally, TagOn owns a perfect management system helping you handle lots of data.
Tagon’s service – Data Annotation
Tagon’s service – Data Annotation
TagOn has the super-diverse Annotation tools. With those advanced tools, you can implement even 18 large-scale project types easily. Besides, TagOn employs an unlimitedly scalable workforce with great skills to meet your scaling-up requirements.
Moreover, the Smart Automatic Labeling Tool of TagOn will help you save time and strengthen accuracy by integrating models which are pre-trained. Last, TagOn will provide you with the Comprehensive Annotation Process to offer consecutive project and crowd management.
Tagon’s service – Data Validation
TagOn helps identify model failures with the Coordinate annotators’ review and TagOn error metrics. Next, TagOn helps minimize failures of your large-scale machine learning outputs by correcting false model predictions perfectly. Finally, TagOn will help you gain machine learning performance insights with visualized investigations for a good expansion.
Why should you choose TagOn – A scaling-up solution for AI data labeling?
TagOn – Data Labeling Platform
Because data labeling is very important to the whole success of your AI projects, you should choose the provider carefully. TagOn is one of the largest data labeling service providers in Vietnam with extensive experience in realizing data labeling projects for AI SMEs and vendors in Vietnam.
With TagOn, you will have reasonable costs when scaling up, steady dataset quality at scale, and an amazing time-booster when scaling up.
For more advice, please contact us at the following information:
Contact information:
Website: https://tagon.ai/en
Linkedin: https://www.linkedin.com/company/tagon-data-labeling
Facebook: https://www.facebook.com/TagOnAi/
Phone number: +84 2466 603 178
Email: contact@tagon.ai
