Tired of sucky weather forecasts?
Want to make the most of those sunny days when they come?
You're probably better off forecasting the weather yourself instead of relying. on the weather channel.
The best thing is, you can get started pretty easily using Neural Prophet. Neural Prophet is a relatively new library that uses Facebooks Prophet time series forecasting package and a Pytorch AR-Net model to produce highly accurate time series forecasts quickly. This makes it easy to build your own weather forecasts and forecast with any other time series style data.
In this video you'll learn how to:
1. Preprocess a weather dataset from Kaggle using Pandas
2. Train a time series forecasting model to predict temperature using Neural Prophet
3. Forecast temperature into the future using the trained model
Get the code: https://github.com/nicknochnack/Forecasting-Weather-with-Neural-Prophet
Chapters:
0:00 - Start
2:22 - Installing and Importing Neural Prophet
3:59 - Reading and Preprocessing Weather Data
14:19 - Training a Neural Prophet Model
16:33 - Generating Forecasts. with Neural Prophet
20:48 - Saving and Reloading Neural Prophet Models
Oh, and don't forget to connect with me!
LinkedIn: https://www.linkedin.com/in/nicholasrenotte
Facebook: https://www.facebook.com/nickrenotte/
GitHub: https://github.com/nicknochnack
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
