Telus international Study Guide Questions and Answers Rated A+

Telus international Study Guide Questions and Answers Rated A+ What is the primary purpose of data annotation in machine learning projects? To label and categorize data for training algorithms. Why is it important to maintain high accuracy in data annotation? Accuracy ensures that machine learning models are trained effectively and perform well. What should you do if you come across ambiguous or unclear data during annotation? Consult the guidelines or seek clarification from a supervisor or team lead. How can you contribute to improving the quality of a dataset in a Telus project? By following the provided guidelines closely and maintaining consistency in your annotations. What is the role of feedback in improving the annotation process? Feedback helps identify mistakes and areas for improvement, ensuring better quality in future tasks. 2 How does annotation help in natural language processing (NLP) tasks? Annotation helps identify patterns and context, which is crucial for NLP models to understand human language. What is a common challenge faced during data annotation? Ensuring that all annotations are consistent and accurate across different datasets and tasks. Why is it important to respect confidentiality when handling client data? Confidentiality protects sensitive information and complies with privacy regulations. How can you ensure that your annotations are consistent over time? By regularly reviewing the guidelines and cross-checking your work for accuracy. What steps should be taken if a project guideline is unclear or incomplete? Seek clarification from a supervisor or consult with team members to ensure correct interpretation. 3 Why is it important to understand the end goal of the project you're working on? Understanding the goal ensures that your annotations align with the overall objectives of the project. What should you do if you encounter irrelevant or offensive content in the data? Follow the project’s guidelines for flagging