GitHub Repository: probml/pyprobml
Path: blob/master/notebooks/book1/20/README.md
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Chapter 20: Dimensionality reduction

Figures

Figure No.	Notebook	Figure
20.1	pcaDemo2d.ipynb	-
20.2	pca_digits.ipynb	-
20.3	pcaImageDemo.ipynb	-
20.4	pca_projected_variance.ipynb	-
20.5	pcaStandardization.ipynb	-
20.6	pcaOverfitDemo.ipynb	-
20.7	pcaOverfitDemo.ipynb	-
20.8	pcaOverfitDemo.ipynb	-
20.9	-	Figure_20.9.png
20.10	pcaEmStepByStep.ipynb	-
20.11	-	Figure_20.11.png
20.12	mixPpcaDemo.ipynb	-
20.13	binary_fa_demo.ipynb	-
20.14	-	Figure_20.14_B.png Figure_20.14_A.png
20.15	-	Figure_20.15.png
20.16	-	Figure_20.16.png
20.17	ae_mnist_tf.ipynb	Figure_20.17_B.png Figure_20.17_A.png
20.18	ae_mnist_tf.ipynb	Figure_20.18_A.png Figure_20.18_B.png
20.19	ae_mnist_tf.ipynb	Figure_20.19_A.png Figure_20.19_B.png
20.20	-	Figure_20.20.png
20.21	ae_mnist_tf.ipynb	Figure_20.21_D.png Figure_20.21_I.png Figure_20.21_A.png Figure_20.21_H.png Figure_20.21_E.png Figure_20.21_C.png Figure_20.21_F.png Figure_20.21_B.png Figure_20.21_G.png
20.22	-	Figure_20.22.png
20.23	-	Figure_20.23.png
20.24	fig_20_24.ipynb	Figure_20.24_A.png Figure_20.24_B.png
20.25	fig_20_25.ipynb	Figure_20.25_A.png Figure_20.25_B.png
20.26	fig_20_26.ipynb	Figure_20.26_B.png Figure_20.26_A.png
20.27	vae_mnist_conv_lightning.ipynb	Figure_20.27_A.png Figure_20.27_B.png
20.28	-	Figure_20.28.png
20.29	-	Figure_20.29_B.png Figure_20.29_A.png Figure_20.29_C.png
20.30	fig_20_30.ipynb	-
20.31	fig_20_31.ipynb	-
20.32	-	Figure_20.32_B.png Figure_20.32_A.png
20.33	fig_20_33.ipynb	-
20.34	manifold_swiss_sklearn.ipynb	-
20.35	kpcaScholkopf.ipynb	-
20.36	fig_20_36.ipynb	-
20.37	fig_20_37.ipynb	-
20.38	fig_20_38.ipynb	-
20.39	-	Figure_20.39.png
20.40	-	Figure_20.40.png
20.41	fig_20_41.ipynb	-
20.42	-	Figure_20.42.png
20.43	-	Figure_20.43.jpg
20.44	-	Figure_20.44_B.png Figure_20.44_A.png
20.45	-	Figure_20.45.png

Supplementary material

Title	Software	Link
PCA	Sklearn	pca.ipynb
Autoencoder for (Fashion) MNIST	TF2	ae_mnist_tf.ipynb
Autoencoder for (Fashion) MNIST (GDL)	TF2	ae_mnist_gdl_tf.ipynb
VAE for CelebA	TF2	vae_celeba_tf.ipynb
VAE for MNIST (GDL)	TF2	vae_mnist_gdl_tf.ipynb
Skipgram with negative sampling (D2L 14.3)	PyTorch	skipgram_torch.ipynb
Word analogies with skipgram (D2L 14.7)	PyTorch	word_analogies_torch.ipynb

Chapter 20: Dimensionality reduction

Figures

Supplementary material

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