You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: README.md
+1-1Lines changed: 1 addition & 1 deletion
Original file line number
Diff line number
Diff line change
@@ -80,7 +80,7 @@ For complete Documentation with tutorials visit [ReadTheDocs](https://pytorch-ta
80
80
81
81
**Semi-Supervised Learning**
82
82
83
-
-[Denoising AutoEncoder](https://www.kaggle.com/code/faisalalsrheed/denoising-autoencoders-dae-for-tabular-data) is an autoencoder which learns robust feature representation, to compensate any noise in the dataset.
83
+
-[Denoising AutoEncoder](https://www.kaggle.com/code/springmanndaniel/1st-place-turn-your-data-into-daeta) is an autoencoder which learns robust feature representation, to compensate any noise in the dataset.
84
84
85
85
## Implement Custom Models
86
86
To implement new models, see the [How to implement new models tutorial](https://github.com/manujosephv/pytorch_tabular/blob/main/docs/tutorials/04-Implementing%20New%20Architectures.ipynb). It covers basic as well as advanced architectures.
0 commit comments