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Model Visualisation

With Python and R Code

Though visualisation is used in data science to understand the shape of the data (data-vis), it is not widely used for the models developed; which are largely evaluated based on numerical summaries. Model visualisation (model-vis) can help understand: the shape of the model, the impact of parameters & different input data on the model, the fit of the model & where it can be improved.


1. Introduction

2. Learning and Layers

3. n/p/N Challenge

4. Regression: Small

(p = 10, n < 1K)

5. Regression: N Models

(p = 10, n < 10K, model = 50)

6. Classification: 2 Class

(p = 10, n < 100K, class = 2)

7. Classification: 10 Class

(p = 10, n < 100K, class = 10)

8. Classification: Large

(p = 10, n ~ 1M)

9. Clustering

10. Code and Talks

11. About the Author

12. Credit