Climate Change Forecasting Using Deep Learning

提供方
Coursera Project Network
在此指导项目中,您将:

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中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

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

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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)

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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