Inspiration
The food data set of i tradenetwork
What it does
Predicts the failed case rate of inspection based on parameters of vendor, shipping warehouse, month shipped, and category of product
How I built it
Using tensorflow.js to build model based on parameters Threw a bunch of data into it
Challenges I ran into
accidentally fell asleep for 2 hours tensorflow.js is not nice to me
Accomplishments that I'm proud of
Learned basics of tensorflow and machine learning I got predictive number at the end based on testcases
What I learned
ml is hard
What's next for ITradeNetwork Case Failure Prediction Model
vendor score, integration with la city data set, world domination
Built With
- itradenetwork
- node.js
- tensorflow.js
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