From the course: Data Science Methodologies: Making Business Sense
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Challenge 1
From the course: Data Science Methodologies: Making Business Sense
Challenge 1
(upbeat music) - Ready for a challenge? There is a data set about cars at the URL shown here. And the challenge is to come up with an app that uses this data to help car buyers, or sellers, get a prediction on the acceptability of a car they are interested in. Follow this Chrome approach build a minimum viable product, and deploy it on your local host. Here are some hints to get started. First, write the user story that helps you identify who is your target user, what they want and why. Then, break it down to smaller, more specific data scientists stories. Something that helps you narrow down the scope of work that can be accomplished in less than one sprint. And then, take that story through one full sprint. In that sprint, understand and prepare the data, then train and evaluate a model, and then deploy to be consumed in an app. Since this is our first sprint focus, on getting a minimum viable product using minimum…
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