Review Week 9

This week we will:

  • We have filled the database with the current real data from mibici, which are nearly about 276 stations
  • We have predicted bike availabilities per station (next day prediction). Here it is a data visualization.

Screen Shot 2019-03-15 at 16.04.19.png

  • We have refactored the backend (5 endpoints)
  • We have documented in postman

Week 4 Review

This week so far, we did and delivered the following:

  • Backlog with detailed tasks for every sprint planning:
  • As well, we have redesigned the problem:
    • Now we will analyze clusters of respective regions, neighborhoods in every city which must have MiBici.
    • The new model which we are going to implement will be a Bayesian Classification/Markov Chains instead of the Multinomial Logistic Regression.
    • We are analyzing several solutions in Python, one that we have considered so far is the Random Forest algorithm.
  • We have defined the team organizationScreen Shot 2019-02-10 at 21.44.43