Time Series Is Everywhere—Here’s How to Actually Forecast It
hackernoon.comTime series isn’t just about ARIMA models anymore. LSTM, GRU, and even Q-learning can forecast prices, detect faults, and outsmart classic baselines. This article dives into how—and why—you should care.


What’s the Deal with Time Series?
Time series data is everywhere: stock prices, temperature readings, website traffic, ECG signals—if it has a timestamp, it’s a time series.
Traditional statistical models like ARIMA or Exponential Smoothing get the job done for basic trends. But let’s be real—today’s data is noisy, nonlinear, and often spans multiple variables. That’s where machine learning (ML) and deep learning (DL) flex their muscles.
A Quick Look at Traditional Approaches
Method |
Strengths |
Weaknesses |
---|---|---|
ARIMA |
Easy to interpret, good for linear trends |
Struggles with non-linear patterns |
Prophet |
Easy to use, handles holidays/seasons |
Not great with noisy multivariate data |
But when you’re ...
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