How can I visualize machine learning models in Python?

How can I visualize machine learning models in Python?

You can use libraries like Matplotlib, Seaborn, and Plotly to visualize your machine learning models in Python.

Can you give me an example of using Matplotlib for this?

Sure! You can plot the decision boundary of a classifier using Matplotlib. Would you like a code snippet?

Yes, please! That would be helpful.

Here's a simple example:

import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression

# Create a dataset
X, y = make_classification(n_samples=100, n_features=2, n_classes=2)

# Train a logistic regression model
model = LogisticRegression()
model.fit(X, y)

# Plotting decision boundary
xx, yy = np.meshgrid(np.linspace(X[:, 0].min(), X[:, 0].max(), 100),
                     np.linspace(X[:, 1].min(), X[:, 1].max(), 100))
Z = model.predict(np.c_[xx.ravel(), yy.ravel()])
Z = Z.reshape(xx.shape)
plt.contourf(xx, yy, Z, alpha=0.8)
plt.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k')
plt.title('Decision Boundary')
plt.show()

That looks great! How can I customize the plot further?

You can customize the plot by changing colors, adding labels, and adjusting the title. Would you like specific examples?