Create a Venn Diagram Using Python
If you want to draw a venn diagram using Python, try matplotlib-venn.
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Visualization
Pyvis: Visualize Interactive Network Graphs in Python
If you to create an interactive network graph in a few lines of Python code, use Pyvis.
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Visualize Hyperparameter Connections with HiPlot
When fine-tuning the hyperparameters of your machine learning model, it can be challenging to comprehend the connections between various combinations of hyperparameters and a particular metric.
With HiPlot, you can create parallel plots to understand the relationships within your data in a few lines of Python code.
Play with the plot above here.
Link to HiPlot.
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Lux: A Python API for Intelligent Visual Discovery
Have you ever taken a while to come up with the visualizations for your data? With Lux, you can get some suggestions on what to visualize.
To use Lux, simply import it.
Link to Lux.
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dtreeviz: Visualize and Interpret a Decision Tree Model
If you want to find an easy way to visualize and interpret a decision tree model, use dtreeviz.
The image above shows the output of dtreeviz when applying it to DecisionTreeClassifier.
Code.
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Validation Curve: Determine if an Estimator Is Underfitting Over Overfitting
To find the hyperparameter where the estimator is neither underfitting nor overfitting, use Yellowbrick’s validation curve.
As we can see from the plot above, although max_depth > 2 has a higher training score but a lower cross-validation score. This indicates that the model is overfitting.
Thus, the sweet spot will be where the cross-validation score neither increases nor decreases, which is 2.
My full article about Yellowbrick.
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Automatically Adjust Annotations in Matplotlib for Readability
If you want to automatically adjust annotations in a matplotlib plot for readability, use the library adjustText.
Link to adjustText.
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ipyvizzu-story: Create an Interactive Presentation in Your Jupyter Notebook
If you want to create an interactive presentation using Python in your Jupyter Notebook, try ipyvizzu-story.
Link to ipyvizzu-store.
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SHAP: Explain Any Machine Learning Model in Python
If you want to explain the output of your machine learning model, use SHAP. In the code above, I use SHAP’s summary plot to visualize the overall impact of features in a DataFrame.
Link to SHAP.
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squarify: Plot Treemap in Python
A treemap splits a rectangle into sub-rectangles, whose sizes are proportional to their values. To plot a treemap in Python, use squarify.
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