Size: 1.35 GB
Build a weather predictor using python
What you’ll learn
- Build a weather predictor using python.
Use autocorrelation to build time-series features.
Detect and remove seasonal trends.
- Handle missing values.
- Download and ingest csv-formatted data.
- Handle dates in with a custom python converter.
- Evaluate a time-series model’s performance.
- Some experience with python is helpful, but not required.
DescriptionWelcome! In this course, we’ll walk through every step of making your own weather predictor. We’ll find weather data, explore it and get it in order. We’ll use the modeling tools of deseasonalization and linear regression to predict temperatures at the beach. We’ll use the statistical tools of autoregression and confidence intervals to guide our feature selection and apply our results. And we’ll code the whole thing up from scratch in python and organize it to be easy to read and easy to extend.
- Machine learning students and data scientists seeking project-based time series modeling and autocorrelation instruction.