Updated README

dillondaudert · May 26, 2021 · ca5fbea · ca5fbea
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diff --git a/PlotMNIST.jl.html b/PlotMNIST.jl.html
diff --git a/README.md b/README.md
@@ -67,7 +67,7 @@ The low-dimensional embedding is initialized (by default) with the eigenvectors
 - If you're familiar with [t-SNE](https://lvdmaaten.github.io/tsne/), then [this page](https://jlmelville.github.io/uwot/umap-for-tsne.html) describes UMAP with similar vocabulary to that dimension reduction algorithm
 
 ## Examples
-The full MNIST and FMNIST datasets are plotted below using both this implementation and the [Python implementation](github.com/lmcinnes/umap) for comparison. These were generated by [this notebook](PlotMNIST.ipynb).
+The full MNIST and FMNIST datasets are plotted below using both this implementation and the [Python implementation](github.com/lmcinnes/umap) for comparison. These were generated by [this Pluto notebook](PlotMNIST.jl).
 
 Note that the memory allocation for the Python UMAP is unreliable, as Julia's benchmarking doesn't count memory allocated within Python itself.
 ### MNIST