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Unsupervised learning

• jointpdf 7y ago
  In my experience, unsupervised learning is more broadly useful (and easier to implement) than supervised learning. Use it for data exploration, data validation, anomaly detection, topic modeling, recommender systems, cluster analysis, etc. Recommended algorithms: - UMAP (https://github.com/lmcinnes/umap/blob/master/README.rst https://github.com/lmcinnes/umap/blob/master/README.rst) - HDBSCAN (https://github.com/scikit-learn-contrib/hdbscan/blob/master/README.rst https://github.com/scikit-learn-contrib/hdbscan/blob/master/...) - MatrixProfile (https://github.com/target/matrixprofile-ts/blob/master/README.md https://github.com/target/matrixprofile-ts/blob/master/READM...) - NMF (https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF https://scikit-learn.org/stable/modules/generated/sklearn.de...)
  • swayson 7y ago
    Totally agree. Such a useful set of tools. Here is an insightful talk about the application of UMAP to learn embeddings for the folks who are interested: https://www.youtube.com/watch?v=OtVR_ZnXLu4 https://www.youtube.com/watch?v=OtVR_ZnXLu4