Capstone project for Udacity Machine Learning Nanodegree
- Number of instances: 19,735
- Number of attributes: 29
- date: year-month-day hour:minute:second
- T1: Temperature in kitchen area, in Celsius
- RH_1: Humidity in kitchen area, in %
- T2: Temperature in living room area, in Celsius
- RH_2: Humidity in living room area, in %
- T3: Temperature in laundry room area
- RH_3: Humidity in laundry room area, in %
- T4: Temperature in office room, in Celsius
- RH_4: Humidity in office room, in %
- T5: Temperature in bathroom, in Celsius
- RH_5: Humidity in bathroom, in %
- T6: Temperature outside the building (north side), in Celsius
- RH_6: Humidity outside the building (north side), in %
- T7: Temperature in ironing room, in Celsius
- RH_7: Humidity in ironing room, in %
- T8: Temperature in teenager room 2, in Celsius
- RH_8: Humidity in teenager room 2, in %
- T9: Temperature in parents’ room, in Celsius
- RH_9: Humidity in parents’ room, in %
- T_out: Temperature outside (from Chievres weather station), in Celsius
- Pressure: (from Chievres weather station), in mm Hg
- RH_out: Humidity outside (from Chievres weather station), in %
- Wind speed: (from Chievres weather station), in m/s
- Visibility: (from Chievres weather station), in km
- T_dewpoint: (from Chievres weather station), °C
- rv1: Random variable 1, non-dimensional
- rv2: Random variable 2, non-dimensional
- Lights: energy use of light fixtures in the house in Wh
- Appliances: energy use in Wh (Target Variable)
Python version: 3.5
The software requirements are mentioned in the requirements.txt
file in top level directory. To install these dependencies, use
the command:-
pip3 install -r requirements.txt
The installation of SciPy would fail on Windows because of absence of Numpy + MKL. To install dependencies on windows, follows the steps:-
- Download NumPy + MKL for the mentioned python version from here.
- Remove the Numpy's entry from
requirements.txt. - Run the command:
pip3 install -r requirements.txt.
To run the software, navigate to the top level directory and type
jupyter notebook predict_energy_consumption.ipynb