Inspiration
- We wanted to know what contributes to a 'good' quality wine, so we decided to explore some input variables and see how it correlated with people's scores on red wine quality. ## What it does
- This project we build classification model to predict whether a wine will be categorizes as 'good' or not. ## How we built it
- We used SingleStore notebook to run python and SQL scripts. We implemented Logistic Regression and KNN Classification to predict whether a wine is good or not. ## Challenges we ran into
- At first we wanted to design an app using React so we can input data and generate our predictive result at the front end. However, we have minimum understanding about Node and building front end app so we ended up just quitting, One other challenge that we ran into is to identify questions that we want to answer. We were a bit lost because we do not have a clear goal on what we want to do. ## Accomplishments that we're proud of
- We were proud of our predictive results as we are able to achieve an accuracy score of over 80%. ## What we learned
- We learned how to implement and classification models in Python and boost our accuracy scores. ## What's next for Predictive Analysis on Wine Quality Data
- Hopefully, next time we can create an APP using react, node, or javascript and deploy our machine learning model.
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