Climate Change Forecasting Using Deep Learning

提供方
Coursera Project Network
在此指導項目中,您將:

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
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Deep Learning
  • Artificial Intelligence (AI)
  • visualization
  • Machine Learning
  • Time Series Modelling

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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)

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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