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

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