I am quite new to predictive modelling but have knowledge of GIS, R, python, SQL, etc.I am currently doing a project in work trying to predict when parking spaces will be available based on data received from a mobile phone application.I have 2 sql tablesParkingTickets ParkingTicketId  (Integer)ParkingAreaId    (Integer)Latitude (Integer)Longitude    (Integer)Location (Text)ParkingDate  (DateTime)DurationInMinutes    (Integer)ExpiryDate   (DateTime)Day (Text)ParkingAreas:ParkingAreaId (Integer)MaxSpaces (Integer)Main assumption is that only app users can park in the 18 parking lots (both on-street and off-street lots (no multi store or underground)). I do not take in to account user preference, weather, events, etc., etc. This is purely presence and absence based on data at hand. I have researched techniques and was looking into using a birth/death model but struggling to find examples of it in use.Any help or pointers on models to use would be brilliant!sample data: ParkingTicketId    ParkingAreaId   Latitude    Longitude   Date    DurationInMinutes   ExpiryDate  Day60465   302 42.56246869 -70.91313754    2014/03/07 16:36    5   2014/03/07 16:41    Friday60466   302 42.57139883 -70.91906364    2014/03/07 16:36    23  2014/03/07 16:59    Friday60467   302 42.54419925 -70.9417496 2014/03/07 16:36    24  2014/03/07 17:00    Friday60472   302 42.57576595 -70.92876607    2014/03/07 16:36    16  2014/03/07 16:52    Friday60477   302 42.55573294 -70.92912634    2014/03/07 16:36    9   2014/03/07 16:45    Friday60479   302 42.55711998 -70.91200458    2014/03/07 16:36    19  2014/03/07 16:55    Friday60480   302 42.58008043 -70.91559081    2014/03/07 16:37    5   2014/03/07 16:42    Friday60485   302 42.55161223 -70.9240808 2014/03/07 16:37    21  2014/03/07 16:58    Friday60492   302 42.58437849 -70.92764527    2014/03/07 16:37    6   2014/03/07 16:43    FridayParkingAreaId   MaxSpaces302 8304 50306 95308 30
Parking Prediction based on Mobile application
machine learning;python;r;predictive modeling