My example pull request title

[smith-kyle]

No description provided.

[gitnotebooks]

Found 1 changed notebook. Review the changes at https://app.gitnotebooks.com/GitNotebooks/demo/pull/3

[gitnotebooks-staging]

Found 1 changed notebook. Review the changes at https://app-staging.gitnotebooks.com/GitNotebooks/demo/pull/3

[paulmlv-upstart]

LGTM overall, a few questions.

[paulmlv-upstart]

Commented on notebook sklearn-example-2.ipynb Cell 1 Line 1

# Introducing Scikit-Learn

Optional: Add API link.

[paulmlv-upstart]

Commented on notebook sklearn-example-2.ipynb Cell 10 Line 4

plt.scatter(data_projected[:, 0], data_projected[:, 1], c=digits.target,
            edgecolor='none', alpha=0.5,
            cmap=plt.cm.get_cmap('spectral', 10))
plt.colorbar(label='digit label', ticks=range(10))

Why range(10)?

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 3 Line 5

import seaborn as sns
from utils import summarize_dataframe

iris = sns.load_dataset('iris')

test

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 5 Line 2

iris['PCA1'] = X_2D[:, 0]
iris['PCA2'] = X_2D[:, 1]

test

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 7 Line 1

### Unsupervised learning: Dimensionality reduction

test

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 8 Line 2

from sklearn.manifold import Isomap
iso = Isomap(n_components=2)

test

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 8 From line 2 to 4

iso = Isomap(n_components=2)
iso.fit(digits.data)
data_projected = iso.transform(digits.data)

test

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 3 Line 1

import seaborn as sns

test

[smith-kyle]

Commented on notebook sklearn-example-2.ipynb Cell 3 Line 2

import seaborn as sns
from utils import summarize_dataframe

test