Alternatives and similar repositories for modern-deep-learning-tabular-data

Users that are interested in modern-deep-learning-tabular-data are comparing it to the libraries listed below

• gkunapuli / ensemble-methods-notebooks
  A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)
  ☆92Updated 2 years ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆70Updated this week
• tblume1992 / MFLES
  ☆115Updated last year
• ml-for-high-risk-apps-book / Machine-Learning-for-High-Risk-Applications-Book
  Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
  ☆103Updated 2 years ago
• tunguz / TabularBenchmarks
  ☆201Updated last month
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆50Updated 3 years ago
• ip200 / venn-abers
  Python implementation of binary and multi-class Venn-ABERS calibration
  ☆191Updated last month
• PacktPublishing / The-Kaggle-Workbook
  Code Repository for The Kaggle Workbook, Published by Packt
  ☆136Updated last week
• marcopeix / TimeSeriesForecastingUsingFoundationModels
  Official repository for the book Time Series Forecasting with Foundation Models
  ☆30Updated last month
• donlapark / coverforest
  A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.
  ☆44Updated 3 months ago
• NextBrain-ai / nbsynthetic
  nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets
  ☆69Updated 2 years ago
• ysraell / forecasting
  Forecasting: Principles and Practice
  ☆61Updated 4 years ago
• kathrinse / TabSurvey
  Experiments on Tabular Data Models
  ☆282Updated 2 years ago
• aruberts / TabTransformerTF
  TensorFlow implementation of TabTransformer
  ☆85Updated 2 years ago
• PacktPublishing / Applied-Machine-Learning-Explainability-Techniques
  Applied Machine Learning Explainability Techniques, published by Packt
  ☆246Updated last week
• solegalli / feature_engine
  Feature engineering package with sklearn like functionality
  ☆55Updated last year
• atreadw1492 / software_engineering_for_data_scientists
  ☆12Updated 2 years ago
• PacktPublishing / Interpretable-Machine-Learning-with-Python-2E
  Interpretable ML with Python, 2E - published by Packt
  ☆103Updated last week
• Carl-McBride-Ellis / TOBoML
  The Orange Book of Machine Learning
  ☆50Updated 2 months ago
• maxmekiska / imbrium
  Standard and Hybrid Deep Learning Multivariate-Multi-Step & Univariate-Multi-Step Time Series Forecasting.
  ☆61Updated last year
• mattharrison / effective_xgboost_book
  ☆292Updated 2 years ago
• AidanCooper / shap-analysis-guide
  How to Interpret SHAP Analyses: A Non-Technical Guide
  ☆57Updated 4 years ago
• dorukcanga / AutoFeatSelect
  A python library to automate feature selection process for machine learning projects.
  ☆64Updated 2 years ago
• lmassaron / Machine-Learning-on-Tabular-Data
  Code for the new Manning book on machine learning on tabular datasets
  ☆62Updated 9 months ago
• dholzmueller / pytabkit
  ML models + benchmark for tabular data classification and regression
  ☆293Updated 2 weeks ago
• PacktPublishing / Practical-Guide-to-Applied-Conformal-Prediction
  Practical Guide to Applied Conformal Prediction, published by Packt
  ☆193Updated last week
• trainindata / feature-engineering-for-time-series-forecasting
  Code repository for the online course "Feature Engineering for Time Series Forecasting".
  ☆192Updated last year
• lmassaron / deep-learning-for-tabular-data
  An updated (2025) guide to Deep Learning for tabular data, comparing a fine-tuned Keras 3 (PyTorch backend) DNN and an Optuna-optimized…
  ☆47Updated 2 months ago
• MartinWeigl / pycaleva
  A framework for calibration measurement of binary probabilistic models
  ☆29Updated last year
• superlinear-ai / conformal-tights
  👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
  ☆114Updated last month