doi.bio/leland_mcinnes


Leland McInnes

Leland McInnes is a senior researcher at the Tutte Institute for Mathematics and Computing. His work focuses on unsupervised learning and topological data analysis.

Education

McInnes received his education at the National Institute for Research in Computer Science and Control, Carnegie Mellon University, Bielefeld University, University of California, Berkeley, and Université Catholique de Louvain - UCLouvain.

Publications

McInnes has published several papers on dimensionality reduction techniques, manifold learning, and clustering algorithms. Some of his notable works include:

Youtube Videos

Youtube Title: Leland McInnes - Data Mapping for Data Exploration | PyData Seattle 2023

Youtube Link: link

Youtube Channel Name: PyData

Youtube Channel Link: https://www.youtube.com/@PyDataTV

Leland McInnes - Data Mapping for Data Exploration | PyData Seattle 2023

Youtube Title: A Bluffer's Guide to Dimension Reduction - Leland McInnes

Youtube Link: link

Youtube Channel Name: PyData

Youtube Channel Link: https://www.youtube.com/@PyDataTV

A Bluffer's Guide to Dimension Reduction - Leland McInnes

Youtube Title: High Quality, High Performance Clustering with HDBSCAN | SciPy 2016 | Leland McInnes

Youtube Link: link

Youtube Channel Name: Enthought

Youtube Channel Link: https://www.youtube.com/@enthought

High Quality, High Performance Clustering with HDBSCAN | SciPy 2016 | Leland McInnes

Youtube Title: Leland McInnes, John Healy | Clustering: A Guide for the Perplexed

Youtube Link: link

Youtube Channel Name: PyData

Youtube Channel Link: https://www.youtube.com/@PyDataTV

Leland McInnes, John Healy | Clustering: A Guide for the Perplexed

Youtube Title: Topology and Language | AI & Topology | Leland McInnes

Youtube Link: link

Youtube Channel Name: Applied Machine Learning Days

Youtube Channel Link: https://www.youtube.com/@AppliedMachineLearningDays

Topology and Language | AI & Topology | Leland McInnes

Youtube Title: MIA: Leland McInnes, Low dim embeddings of words and docs; Hoon Cho, Density-aware visualization

Youtube Link: link

Youtube Channel Name: Broad Institute

Youtube Channel Link: https://www.youtube.com/@broadinstitute

MIA: Leland McInnes, Low dim embeddings of words and docs; Hoon Cho, Density-aware visualization

Youtube Title: M4CSA Leland McInnes: UMAP Theory and Practice

Youtube Link: link

Youtube Channel Name: M4CSA Seminar

Youtube Channel Link: https://www.youtube.com/@m4csaseminar579

M4CSA Leland McInnes: UMAP Theory and Practice

Youtube Title: Leland Mcinnes: Topological Techniques for Unsupervised Learning | PyData LA 2019

Youtube Link: link

Youtube Channel Name: PyData

Youtube Channel Link: https://www.youtube.com/@PyDataTV

Leland Mcinnes: Topological Techniques for Unsupervised Learning | PyData LA 2019

Youtube Title: "Learning Topology: Topological Approaches for Unsupervised Learning" by Leland McInnes

Youtube Link: link

Youtube Channel Name: PyData Montreal

Youtube Channel Link: https://www.youtube.com/@PyDataMontreal

"Learning Topology: Topological Approaches for Unsupervised Learning" by Leland McInnes

Youtube Title: Algo Hour - Nearest Neighbor Descent (and friends) | Dr. Leland McInnes

Youtube Link: link

Youtube Channel Name: Stitch Fix Multithreaded

Youtube Channel Link: https://www.youtube.com/@stitchfixmultithreaded5212

Algo Hour - Nearest Neighbor Descent (and friends) | Dr. Leland McInnes

Youtube Title: Vectors & Embeddings Roundtable

Youtube Link: link

Youtube Channel Name: OpenTeams

Youtube Channel Link: https://www.youtube.com/@openteams6924

Vectors & Embeddings Roundtable

Youtube Title: Moving towards KDearestNeighbors with Leland McInnes - creator of UMAP

Youtube Link: link

Youtube Channel Name: :probabl.

Youtube Channel Link: https://www.youtube.com/@probabl_ai

Moving towards KDearestNeighbors with Leland McInnes - creator of UMAP

Youtube Title: PyData Ann Arbor: Leland McInnes | PCA, t-SNE, and UMAP: Modern Approaches to Dimension Reduction

Youtube Link: link

Youtube Channel Name: PyData

Youtube Channel Link: https://www.youtube.com/@PyDataTV

PyData Ann Arbor: Leland McInnes | PCA, t-SNE, and UMAP: Modern Approaches to Dimension Reduction

Youtube Title: Leland McInnes & John Healy | The Python Exchange for DOE Employees (DOEPy) 2-22-2023

Youtube Link: link

Youtube Channel Name: Don't Use This Code • James Powell

Youtube Channel Link: https://www.youtube.com/@dutctv

Leland McInnes & John Healy | The Python Exchange for DOE Employees (DOEPy) 2-22-2023

Youtube Title: How To Use UMAP and HDBScan To Surface Insights and Discover Issues

Youtube Link: link

Youtube Channel Name: Arize AI

Youtube Channel Link: https://www.youtube.com/@arizeai

How To Use UMAP and HDBScan To Surface Insights and Discover Issues

Youtube Title: Panel discussion with Q&A session | AI & Topology

Youtube Link: link

Youtube Channel Name: Applied Machine Learning Days

Youtube Channel Link: https://www.youtube.com/@AppliedMachineLearningDays

Panel discussion with Q&A session | AI & Topology

Youtube Title: DataMapPlot for building data maps of your clustered data

Youtube Link: link

Youtube Channel Name: Rajistics - data science, AI, and machine learning

Youtube Channel Link: https://www.youtube.com/@Rajistics

DataMapPlot for building data maps of your clustered data

Youtube Title: UMAP Uniform Manifold Approximation and Projection for Dimension Reduction | SciPy 2018 |

Youtube Link: link

Youtube Channel Name: Enthought

Youtube Channel Link: https://www.youtube.com/@enthought

UMAP Uniform Manifold Approximation and Projection for Dimension Reduction | SciPy 2018 |