Centre for Environmental Planning & Technology (CEPT) University
Bachelor of Technology, Construction Technology
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I labeled over 5,000 data points related to common customer complaints and product questions, focusing on intent classification and entity recognition (e.g., identifying product names, order numbers, and dates). By accurately annotating this data, I helped the model better understand the nuances of customer language, reducing misinterpretations by 25% in pilot tests. I designed and tested a series of chain-of-thought prompts to guide the chatbot to break down complex problems. This allowed it to provide multi-step solutions rather than a single, generic response. I also created zero-shot prompts to test the model's ability to handle completely new queries it hadn't been trained on, helping me identify and fill key knowledge gaps. This proactive approach led to a 15% increase in the model's first-response resolution rate.
Ankur A. hasn’t added any AI Training or Data Labeling experience to their OpenTrain profile yet.
Bachelor of Technology, Construction Technology
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