Using TensorFlow and Long Short-Term Memory Recurrent Neural Networks.
Background: research has shown that temperature, humidity, and wind can be accurately predicted out to 72hrs using a 15 year data period of hourly measurements. Mostly based on this paper.
Set up a Python virtual environment and install requirements via pip:
$ virtualenv venv
$ source venv/bin/activate
$ pip install -r requirements.txt
Scripts:
To download data form Weather Company Data, use tools/weather_data.py > data.csv
. This will download the last year's daily minimum and maximum temperature values for a selected location and save it in data.csv
.
Before use, make sure to sign up for an account with them and add the username and password to the .env
file.
Richard Dancsi
- Blog: wimagguc.com
- Github: github.com/wimagguc
- Twitter: twitter.com/wimagguc
- Linkedin: linkedin.com/in/richarddancsi
- Company: buntlabs.com