TD HOSPITLA

Inspiration

What it does

Read a data sample find important features related to death rate then gathers them and trains a model base don those features to then take a data set and predict the outcome of death.

How we built it

We used panda dataframes as well as tensor flow and scit learn to train and test multiple features

Challenges we ran into

Optimization holds we struggle to increase accuracy passed 90%

Accomplishments that we're proud of

We got the accuracy to 90% lol.

What we learned

The many different way to encode as well as distinguish related features past more that just basic correlation.

What's next for TD HOSPITLA

Built With

• flask
• numpy
• pandas
• python
• scikit-learn
• tensorflow