San Francisco is home to a massive population and is visited by millions of tourists every year. Due to its popular destinations, San Francisco has to manage its public transport and traffic efficiently in order to maintain order in everyday life.

This is not an easy task, so we’ve used Uber data to analyze and predict different route times to 3 of the most popular hotspots in San Francisco; the Palace of Fine Arts, Fisherman’s Wharf, and Oracle Park. Looking into this data should give us some information about travel time trends and what the city can do to decrease travel time.

What it does

We have explored, cleaned, and used our data in our prediction models.

How I built it

Data cleaning, ARIMA/SARIMA, LSTM, Holts

Challenges I ran into

Accomplishments that I'm proud of

What I learned

What's next

Built With

  • keras
  • pain
  • statsmodels
  • tensorflow
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