Update README.md

Author: r0f1

README.md

@@ -25,6 +25,7 @@ Python debugger (pdb) - [blog post](https://www.blog.pythonlibrary.org/2018/10/1
 [qgrid](https://github.com/quantopian/qgrid) - Pandas `DataFrame` sorting.  
 [pivottablejs](https://github.com/nicolaskruchten/jupyter_pivottablejs) - Drag n drop Pivot Tables and Charts for jupyter notebooks.  
 [itables](https://github.com/mwouts/itables) - Interactive tables in Jupyter.  
+[jupyter-datatables](https://github.com/CermakM/jupyter-datatables) - Interactive tables in Jupyter.  
 
 #### Pandas Alternatives and Additions
 [modin](https://github.com/modin-project/modin) - Parallelization library for faster pandas `DataFrame`.  
@@ -161,7 +162,6 @@ Tutorials - [1](https://www.kaggle.com/residentmario/automated-feature-selection
 [sklearn](https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html) - t-distributed Stochastic Neighbor Embedding (t-SNE), [intro](https://distill.pub/2016/misread-tsne/). Faster implementations: [lvdmaaten](https://lvdmaaten.github.io/tsne/), [MulticoreTSNE](https://github.com/DmitryUlyanov/Multicore-TSNE).  
 [FIt-SNE](https://github.com/KlugerLab/FIt-SNE) - Fast Fourier Transform-accelerated Interpolation-based t-SNE.  
 [umap](https://github.com/lmcinnes/umap) - Uniform Manifold Approximation and Projection, [talk](https://www.youtube.com/watch?v=nq6iPZVUxZU), [explorer](https://github.com/GrantCuster/umap-explorer), [explanation](https://pair-code.github.io/understanding-umap/).  
-UMAP does not preserve global structure any better than t-SNE when using the same initialization - [paper](https://www.biorxiv.org/content/10.1101/2019.12.19.877522v1).  
 [scikit-tda](https://github.com/scikit-tda/scikit-tda) - Topological Data Analysis, [paper](https://www.nature.com/articles/srep01236), [talk](https://www.youtube.com/watch?v=F2t_ytTLrQ4), [talk](https://www.youtube.com/watch?v=AWoeBzJd7uQ).  
 [mdr](https://github.com/EpistasisLab/scikit-mdr) - Dimensionality reduction, multifactor dimensionality reduction (MDR).  
 [sklearn](http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html) - Truncated SVD (aka LSA).   
@@ -381,6 +381,7 @@ Understanding SVM Regression: [slides](https://cs.adelaide.edu.au/~chhshen/teach
 [nmslib](https://github.com/nmslib/nmslib) - Similarity search library and toolkit for evaluation of k-NN methods.  
 [buckshotpp](https://github.com/zjohn77/buckshotpp) - Outlier-resistant and scalable clustering algorithm.  
 [merf](https://github.com/manifoldai/merf) - Mixed Effects Random Forest for Clustering, [video](https://www.youtube.com/watch?v=gWj4ZwB7f3o)  
+[tree-SNE](https://github.com/isaacrob/treesne) - Hierarchical clustering algorithm based on t-SNE.  
 
 #### Interpretable Classifiers and Regressors
 [skope-rules](https://github.com/scikit-learn-contrib/skope-rules) - Interpretable classifier, IF-THEN rules.