from sklearn.datasets import load_digits
digits = load_digits()
import matplotlib.pyplot as plt
%matplotlib inline

from sklearn.decomposition import PCA

pca = PCA(n_components=2)

pca.fit(digits.data)

digits_pca = pca.transform(digits.data)

digits_pca.shape

plt.scatter(digits_pca[:, 0], digits_pca[:, 1], c=digits.target)

plt.matshow(pca.mean_.reshape(8, 8))
plt.matshow(pca.components_[0].reshape(8, 8))
plt.matshow(pca.components_[1].reshape(8, 8))

from sklearn.manifold import SpectralEmbedding

se = SpectralEmbedding()
digits_se = se.fit_transform(digits.data)

plt.scatter(digits_se[:, 0], digits_se[:, 1], c=digits.target)