Data Labeling
Build High-Quality Labeled Dataset
Building a successful machine learning model requires a large amount of high-quality labeled training data. Having better-labeled data gives you an edge over competitors. And without it, supervised learning is not of any use as there is no way to ensure that a model will predict, analyze, or classify correctly. This makes the choice of data labeling tools an important factor in the success of your machine learning project.
Skyl.ai’s powerful Data Labeling service offers one platform to build custom training datasets quickly for highly accurate machine learning models.
How Labelwise works
Image Classification
Labeling Job
- Image classification labeling jobs help you to enrich your training data by labeling images. It deals with the annotation of images by providing a broad categorization of an image.
- Skyl.ai offers a simple interface for image classification labeling jobs that allow you to get your dataset labeled accurately, determining the precision of your machine learning model.
Named Entity Extraction
Labeling Job
- Named entity extraction jobs extract information or named entities from unstructured text into pre-defined categories. The categories of extracted entities could be from people, organizations, and brands to quantities, monetary values, or percentages.
- Skyl.ai NER labeling jobs allow you to create jobs to easily label, tag, and annotate text and improve a machine learning model’s accuracy.
Object Detection
Labeling Job
- Object detection labeling jobs use a bounding box to obtain the specific positions of relevant objects in an image and label them. This includes multiple targets in an image such as vehicles, roads, traffic lights, pedestrians, etc.
- With Skyl.ai Labelwise Object detection job, the collaborators (human labelers) get an intuitive labeling tool to annotate bounding boxes for objects on images. The annotated dataset can then be downloaded as your preferred choice of format YOLO, PASCAL. TF Record.
Text Classification
Labeling Job
- Text classification organizes and categorizes documents or text into predefined categories. The process is used to analyze and identify sentiments within textual data.
- Skyl.ai text classification labeling job enables sorting texts into categories that can be defined with easy and flexible annotation options.
