Alternatives and similar repositories for tutorial_mapper

Users that are interested in tutorial_mapper are comparing it to the libraries listed below

• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆29Updated 5 years ago
• wilsonjr / ClusterShapley
  Explaining dimensionality results using SHAP values
  ☆55Updated 10 months ago
• almost-matching-exactly / DAME-FLAME-Python-Package
  A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data
  ☆62Updated 4 months ago
• slds-lmu / iml_methods_limitations
  Seminar on Limitations of Interpretable Machine Learning Methods
  ☆57Updated 5 years ago
• ksanjeevan / mapper-tda
  Mapper implementation (Topological Data Analysis) in Python
  ☆63Updated 7 years ago
• jmkuebler / auto-tst
  AutoML Two-Sample Test
  ☆19Updated 3 years ago
• chlubba / op_importance
  Compute set of important operations for HCTSA code
  ☆27Updated 5 years ago
• rrtucci / JudeasRx
  python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.
  ☆25Updated 2 years ago
• adalmia96 / umap-mnn
  ☆23Updated 3 years ago
• neurodata / SPORF
  This is the implementation of Sparse Projection Oblique Randomer Forest
  ☆101Updated last year
• bradyneal / causal-inference-books
  Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…
  ☆60Updated 6 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆23Updated 2 years ago
• dbenielli / scikit-multimodallearn
  This Python package implements algorithms for multiviews (multimodals) learning
  ☆14Updated last year
• vcerqueira / MLforForecasting
  Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters
  ☆41Updated 6 years ago
• neurodata / df-dn-paper
  Conceptual & empirical comparisons between decision forests & deep networks
  ☆18Updated 6 months ago
• benedekrozemberczki / spatiotemporal_datasets
  Spatiotemporal datasets collected for network science, deep learning and general machine learning research.
  ☆61Updated last year
• lordgrilo / AML-days-TDA-tutorial
  ☆32Updated 6 years ago
• TutteInstitute / vectorizers
  Vectorizers for a range of different data types
  ☆103Updated last month
• realrate / Causing
  Causing: CAUsal INterpretation using Graphs
  ☆60Updated 2 weeks ago
• lrjball / shap
  A game theoretic approach to explain the output of any machine learning model.
  ☆14Updated 3 years ago
• max-little / GRAPL
  GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference
  ☆83Updated 11 months ago
• malmgrek / gammy
  Generalized additive models in Python with a Bayesian twist
  ☆78Updated 3 months ago
• jwmueller / KDD20-tutorial
  Tutorial on Automated Machine Learning at KDD 2020
  ☆55Updated 5 years ago
• luisroque / bayesian_time_series
  Machine Learning models using a Bayesian approach and often PyMC3
  ☆25Updated 4 years ago
• sfme / RVAE_MixedTypes
  Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)
  ☆50Updated 5 years ago
• AlxndrMlk / blogs-code
  Code for blog posts.
  ☆20Updated 2 years ago
• timsainb / ParametricUMAP_paper
  Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep…
  ☆152Updated 4 years ago
• ciortanmadalina / high_noise_clustering
  Techniques to cluster very noisy data (dropouts or random noise)
  ☆66Updated 6 years ago
• anonICLR2020 / node
  ☆26Updated 6 years ago
• hrayrhar / T-CorEx
  Implementation of linear CorEx and temporal CorEx.
  ☆36Updated 4 years ago