Intermediate · Data

Time Series Forecasting

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. Using historical data points to predict future values in a sequence over time.

Technical Definition

Using historical data points to predict future values in a sequence over time.

How it works

Time series forecasting involves building predictive models that account for temporal dependencies in data. This is crucial for applications like stock market prediction, weather forecasting, and demand planning. Techniques range from statistical methods like ARIMA to deep learning models like RNNs and LSTMs.

Related Concepts

• Recurrent Neural Network (RNN) — A neural network with loops that maintain hidden state, designed to process sequential data like text and time series.
• Prediction — The output a trained model produces when given new input data.