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Optimization of Topic Models using Grid Search Method
In this 2-hour long project-based course, you will learn how to optimize a topic model to achieve best fit using Grid Search method. Topic modelling is an efficient unsupervised machine learning tool that aids in analyzing the latent themes from text datasets. But it is also necessary to learn to optimize the models to obtain the best fit model in order to achieve better interpretable themes to gain meaningful insights. In this project you will learn about the statistical parameters to gauge the model quality and create interactive visualization of the themes for a more intuitive evaluation of topic models. The focus of this project is primarily from an application point of view instead of underlying statistical mechanisms.
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 14 (6 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Barsha Saha |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Business Programming |
Tags | Data Science Business Machine Learning Business Essentials |
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Rating | Not enough ratings |
---|---|
Length | 2 weeks |
Effort | 2 Hours |
Starts | Dec 14 (6 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Barsha Saha |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Business Programming |
Tags | Data Science Business Machine Learning Business Essentials |
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