I have been on a journey for the last six months exploring Artificial Intelligence, Machine Learning and Natural Language Processing and how they could be used to enhance the testing experience. I have used k-means clustering an unsupervised learning model to group data about my product together to produce a heat map of the product and the areas that have caused us problems. I would like to share this experience with other testers to show how we could embrace these technologies. I would like to show how it opened up dialog between tester and developer as they talked about the results and I would like to show where I plan to take it in the future building up to labeling data to use a supervised model for more accurate heat maps and show how this could be used to trigger more precise automation.
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