Alternatives and similar repositories for teller:

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

• Techtonique / nnetsauce
  Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks (currently Python & R)
  ☆16Updated last week
• pbiecek / xai_stories
  XAI Stories. Case studies for eXplainable Artificial Intelligence
  ☆29Updated 4 years ago
• yaronshap / GloballyConsistentRules
  Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…
  ☆24Updated 2 years ago
• Brett-Kennedy / CountsOutlierDetector
  Interpretable, intuitive outlier detector intended for categorical and numeric data.
  ☆9Updated 9 months ago
• luisroque / bayesian_time_series
  Machine Learning models using a Bayesian approach and often PyMC3
  ☆24Updated 4 years ago
• trnnick / tsintermittent
  ☆13Updated 2 years ago
• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated 2 years ago
• RamiKrispin / covid19sf
  R package for tracking Covid19 cases in San Francisco
  ☆12Updated last year
• benvancalster / classimb_calibration
  ☆8Updated 3 years ago
• Akai01 / caretForecast
  Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms
  ☆25Updated 2 years ago
• Techtonique / ahead_python
  Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)
  ☆13Updated 6 months ago
• elephaint / hfas
  Hierarchical Forecasting at Scale
  ☆13Updated last year
• mlr-org / mcboost
  Multi-Calibration & Multi-Accuracy Boosting for R
  ☆32Updated 6 months ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 3 years ago
• ModelOriented / DALEX-docs
  Documentation for the DALEX project
  ☆36Updated last year
• rodrigobressan / keras_boston_housing_price
  Keras 101: A simple Neural Network for House Pricing regression
  ☆15Updated 5 years ago
• alexzwanenburg / familiar
  Repository for the familiar R-package. Familiar implements an end-to-end pipeline for interpretable machine learning of tabular data.
  ☆30Updated last month
• AlxndrMlk / blogs-code
  Code for blog posts.
  ☆19Updated last year
• ck37 / ck37r
  R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.
  ☆19Updated 4 months ago
• jphall663 / responsible_xai
  Guidelines for the responsible use of explainable AI and machine learning.
  ☆17Updated 2 years ago
• almost-matching-exactly / R-FLAME
  R Implementation of FLAME, DAME, and other algorithms in the AME framework
  ☆12Updated last year
• amazon-science / causal-forecasting
  ☆13Updated last year
• rizbicki / predictionBands
  R package to compute distribution-free prediction bands using density estimators
  ☆9Updated 3 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated last year
• AdrianAntico / RetroFit
  Automation of feature engineering, machine learning, model evaluation, model interpretation, eda, forecasting, recommender systems and mo…
  ☆16Updated last year
• pyartemis / artemis
  A Python package with explanation methods for extraction of feature interactions from predictive models
  ☆30Updated last year
• robjhyndman / tscompdata
  Time series competition data
  ☆18Updated last year
• tevgeniou / FoundationsML
  ☆12Updated 4 years ago
• vcerqueira / vest
  Automatic Feature Engineering for Time Series
  ☆17Updated 2 years ago
• DiegoUsaiUK / Propensity_Modelling
  Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
  ☆27Updated 2 years ago