Climate Change Forecasting Using Deep Learning

Offered By
Coursera Project Network
In this Guided Project, you will:

Understand the theory and intuition behind Recurrent Neural Networks and LSTM

Build and train the LSTM based time series model

Assess Trained model performance

Clock1 hour
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this hands-on project, we will analyze the change in temperatures across globe from the 17th century till now and build a multivariate deep learning based time series model to forecast the U.S. Average temperature. Predictive models attempt at forecasting future value based on historical data.

Skills you will develop

Deep LearningArtificial Intelligence (AI)visualizationMachine LearningTime Series Modelling

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Understand the Problem Statement and Business Case

  2. Import libraries and datasets

  3. Perform exploratory data analysis

  4. Perform data cleaning

  5. Perform Data Visualization

  6. Prepare the data before model training (Global Data)

  7. Understand the intuition behind LSTM Networks

  8. Build and train LSTM model for predicting global temperature trend (Global Data)

  9. Assess model performance (Global Data)

  10. Prepare the data before model training (U.S. Data)

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

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