Time Series Forecasting in Python – Tutorial for Beginners
This course introduces time series forecasting with Python, covering key components, baseline models, advanced techniques like ARMA, and model evaluation, taught by expert Marco, who provides practical insights and resources.
MAIN POINTS FROM TRANSCRIPT
- Learn time series data components: trend, seasonality, and residuals.
- Build baseline models and advance to ARMA and seasonal ARMA techniques.
- Incorporate exogenous features and generate prediction intervals.
- Evaluate models using cross-validation and select appropriate metrics.
TAKEAWAYS
- Gain foundational knowledge in statistical models for time series forecasting.
- Explore advanced forecasting techniques and practical applications.
- Marco, an expert in the field, provides comprehensive guidance and resources.
- The course is ideal for Python coders new to time series data.