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محتوای ارائه شده توسط HackerNoon. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط HackerNoon یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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The Metrics Resurrections: Action! Action! Action!

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Manage episode 423218799 series 3474148
محتوای ارائه شده توسط HackerNoon. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط HackerNoon یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

This story was originally published on HackerNoon at: https://hackernoon.com/the-metrics-resurrections-action-action-action.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #llms, #conversational-ai, #ai-applications, #ai-agents, #google-assistant, #user-reported-metrics, #hackernoon-top-story, #user-perceived-metrics, and more.
This story was written by: @pmukherjee. Learn more about this writer by checking @pmukherjee's about page, and for more stories, please visit hackernoon.com.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature. However, recent advancements in LLMs allow for the conversion of unstructured user feedback into structured, actionable metrics. This enables teams to better prioritize performance improvement projects by assessing their impact on user perception alongside system-level metrics. While not foolproof, this combined approach provides a more comprehensive understanding of the effectiveness of changes made to conversational AI agents. It's crucial to remember that both types of metrics are valuable for accurately assessing and improving user perception.

  continue reading

316 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 423218799 series 3474148
محتوای ارائه شده توسط HackerNoon. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط HackerNoon یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

This story was originally published on HackerNoon at: https://hackernoon.com/the-metrics-resurrections-action-action-action.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #llms, #conversational-ai, #ai-applications, #ai-agents, #google-assistant, #user-reported-metrics, #hackernoon-top-story, #user-perceived-metrics, and more.
This story was written by: @pmukherjee. Learn more about this writer by checking @pmukherjee's about page, and for more stories, please visit hackernoon.com.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature. However, recent advancements in LLMs allow for the conversion of unstructured user feedback into structured, actionable metrics. This enables teams to better prioritize performance improvement projects by assessing their impact on user perception alongside system-level metrics. While not foolproof, this combined approach provides a more comprehensive understanding of the effectiveness of changes made to conversational AI agents. It's crucial to remember that both types of metrics are valuable for accurately assessing and improving user perception.

  continue reading

316 قسمت

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