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Compare time series predictions of COVID-19 deaths
In this 2-hour long project-based course, you will learn how to preprocess time series data, visualize time series data and compare the time series predictions of 4 machine learning models.You will create time series analysis models in the python programming language to predict the daily deaths due to SARS-CoV-19, or COVID-19. You will create and train the following models: SARIMAX, Prophet, neural networks and XGBOOST. You will visualize data using the matplotlib library, and extract features from a time series data set, perform data splitting and normalization.
To successfully complete this project, learners should have prior Python programming experience, a basic understanding of machine learning, and a familiarity of the Pandas library.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Rating | Not enough ratings |
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Length | 2 weeks |
Effort | 2 hours |
Starts | Dec 28 (5 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Sherif A. Tawfik Abbas |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Programming |
Tags | Data Science Machine Learning |
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Rating | Not enough ratings |
---|---|
Length | 2 weeks |
Effort | 2 hours |
Starts | Dec 28 (5 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Sherif A. Tawfik Abbas |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Programming |
Tags | Data Science Machine Learning |
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