Artificial Intelligence
Handling Multivariate Time Series with RNNs
This course extends the concepts from the first course by introducing multiple time series inputs. It covers how to preprocess, structure, and train RNN models using **two related time series features** from the **Air Quality dataset**. It also includes model evaluation techniques to assess forecasting accuracy.
Python
PyTorch
4 lessons
13 practices
1 hour
Coding and Data Algorithms
Course details
Handling Multivariate Time Series with RNNs Using PyTorch
Preparing Air Quality Time Series Data by Creating DateTime Columns and Handling Missing Values
Cleaning Air Quality Data for Time Series Analysis
Setting DateTime as Index for Time Series Analysis
Visualizing NO2 Levels in Time Series Data
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