Job category:Data Science & Analytics
120 learners

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
TensorFlow
4 lessons
15 practices
1 hour
Badge for Coding and Data Algorithms,
Coding and Data Algorithms

Course details

Understanding and Preprocessing Multivariate Time Series
Creating a DateTime Index for Time Series
Handling Missing Values in Time Series
Setting DateTime as Time Series Index
Visualizing Time Series Pollution Patterns

Previous CourseNext Course: Time Series Forecasting with LSTMs

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