data labelling
1. Scope of the Project This explains what the project is about and why it exists. A beginner data labeling project typically involves: Supporting a machine learning model (e.g., image recognition, text classification, or speech analysis) Working with a well-defined dataset (images, text, audio, or video) Following clear annotation guidelines provided by the project owner Example scope description: The project involved labeling a dataset to support training of a machine learning model for classifying customer feedback into categories such as positive, negative, and neutral. 2. Specific Data Labeling Tasks Performed This is where you describe exactly what you did. Be concrete and task-oriented. Common beginner tasks include: š¼ļø Image Labeling Drawing bounding boxes around objects (e.g., cars, people) Classifying images into categories Tagging attributes (e.g., color, size) š Text Labeling Sentiment analysis (positive/negative/neutral) Categorizing text (e.g., spam vs. not spam) Named entity recognition (identifying names, locations, dates) š§ Audio Labeling Transcribing speech to text Tagging audio segments (e.g., noise, speech, music) š„ Video Labeling Annotating objects frame-by-frame Tracking movement across frames Example task description: I labeled text data by categorizing customer reviews based on sentiment and identifying key topics such as product quality and delivery experience. 3. Project Size (Beginner Level) This explains how much work was done. For beginners, projects are usually moderate and manageable. Typical beginner project sizes: Small: 100 ā 1,000 data points Medium: 1,000 ā 10,000 data points Timeframe: a few days to a few weeks Often done individually or in a small team Example size description: The project consisted of labeling approximately 2,000 text samples over a two-week period. ā Putting It All Together (Sample Answer) The project involved labeling a dataset to support the training of a machine learning model for sentiment analysis. My tasks included reviewing customer reviews and categorizing them as positive, negative, or neutral, as well as tagging key topics mentioned in the text. The project consisted of approximately 2,000 data samples and was completed over a two-week period as an individual contributor. If you want, tell me the type of data (image, text, audio, etc.), and I can help you write a polished description tailored for your CV or portfolio.