Compare time series predictions of COVID-19 deaths


35 ratings

Offered By
In this Guided Project, you will:

Preprocess time series data for various machine learning models

Visualize time series data

Compare the time series predictions of 4 machine learning models

2 hours
No download needed
Split-screen video
Desktop only

By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths. This workflow includes the following steps: how to examine time series data, prepare the data for analysis, train different models and test their performance, and finally use the models to forecast into the future. You will learn how to visualize data using the matplotlib library, extract features from a time series data set, and perform data splitting and normalization. You will create time series analysis models using the python programming language. You will create and train four time series models: SARIMAX, Facebook prophet, neural networks and XGBOOST.

Skills you will develop

  • Time Series Forecasting

  • Machine Learning

  • Feature Engineering

  • Python Programming

  • Time Series Models

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 basics of time series analysis

  2. Explore and prepare the data

  3. Forecasting using SARIMAX

  4. Forecasting using Facebook's Prophet model

  5. Preparing the dataset for XGBOOST and NN

  6. Splitting the dataset, and data normalization

  7. Train the XGBOOST and NN models

  8. Forecast the future

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



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