Deep Learning Can Forecast Time Series. It Just Often Doesn’t Beat the Boring Stuff.

📰 Medium · Data Science

Deep learning can forecast time series, but often doesn't outperform simpler methods like comparing to last year's data, highlighting the importance of baseline models

intermediate Published 22 Apr 2026

Action Steps

Build a simple baseline model using last year's data as a benchmark
Run a deep learning model on your time series data to forecast future values
Compare the performance of the deep learning model to the baseline model using metrics like mean absolute error or mean squared error
Evaluate the complexity and interpretability of both models to determine if the deep learning model is worth the added complexity
Test the robustness of both models to outliers and missing data to ensure reliability

Who Needs to Know This

Data scientists and analysts can benefit from understanding the limitations of deep learning in time series forecasting, and how to properly evaluate its performance against simpler methods

Key Insight

💡 Simple baseline models can be surprisingly effective in time series forecasting, and deep learning models should be carefully evaluated against these baselines