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https://github.com/rakibhhridoy/visualmachinelearning-yellowbrick

Yellowbrick wraps the scikit-learn and matplotlib to create publication-ready figures and interactive data explorations. It is a diagnostic visualization platform for machine learning that allows us to steer the model selection process by helping to evaluate the performance, stability, and predictive value of our models and further assist in diagnosing the problems in our workflow.
https://github.com/rakibhhridoy/visualmachinelearning-yellowbrick

classification hyperparameter-tuning machine-learning model-evaluation model-view-presenter model-visualization python random-forest random-forest-classifier scikit-learn visualization xgboost xgboost-algorithm yellowbrick

Last synced: about 1 month ago
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Yellowbrick wraps the scikit-learn and matplotlib to create publication-ready figures and interactive data explorations. It is a diagnostic visualization platform for machine learning that allows us to steer the model selection process by helping to evaluate the performance, stability, and predictive value of our models and further assist in diagnosing the problems in our workflow.

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README

        

# *Visual Machine Learning With Yellowbrick*
![img1](https://miro.medium.com/max/638/1*AyHyCYAX3viU5kZC3xiN5A.jpeg)
>Yellowbrick helps to visualize our model in different perspective

### Installation
```bash
$ pip install yellowbrick
$ pip install -U yellowbrick
```

## Get Touch With Me
[Linkedin](https://linkedin.com/in/rakibhhridoy)
[RakibHHridoy](https://rakibhhridoy.github.io)