lmassaron / deep-learning-for-tabular-dataLinks
An updated (2025) guide to Deep Learning for tabular data, comparing a fine-tuned Keras 3 (PyTorch backend) DNN and an Optuna-optimized XGBoost model on the Kaggle Amazon Employee Access Challenge
☆47Updated last month
Alternatives and similar repositories for deep-learning-for-tabular-data
Users that are interested in deep-learning-for-tabular-data are comparing it to the libraries listed below
Sorting:
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆90Updated last year
- ☆201Updated 3 weeks ago
- PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in…☆137Updated 7 months ago
- ☆52Updated 2 years ago
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆159Updated 3 years ago
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆579Updated last year
- zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range fr…☆249Updated 3 months ago
- Boosted neural network for tabular data☆216Updated last year
- TabNet for fastai☆124Updated last month
- xverse (XuniVerse) is collection of transformers for feature engineering and feature selection☆118Updated 2 years ago
- Kaggle Pipeline for tabular data competitions☆206Updated last year
- Winning Solution of Kaggle Mechanisms of Action (MoA) Prediction.☆121Updated 3 years ago
- ☆17Updated 3 years ago
- Applied Machine Learning Explainability Techniques, published by Packt☆246Updated last month
- Experiments on Tabular Data Models☆279Updated 2 years ago
- Modification of TabNet as suggested in the Medium article, "The Unreasonable Ineffectiveness of Deep Learning on Tabular Data"☆62Updated 2 years ago
- Developmental tools to detect data drift☆18Updated last year
- Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networks☆25Updated 5 years ago
- Nested cross-validation for unbiased predictions. Can be used with Scikit-Learn, XGBoost, Keras and LightGBM, or any other estimator that…☆64Updated 5 years ago
- A power-full Shapley feature selection method.☆211Updated last week
- A Tensorflow 2.0 implementation of TabNet.☆244Updated 2 years ago
- ☆101Updated 3 weeks ago
- Example usage of scikit-hts☆57Updated 3 years ago
- References to the Medium articles☆87Updated 2 years ago
- SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.☆153Updated 6 months ago
- Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.☆41Updated 2 years ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆312Updated 5 months ago
- Scikit-learn compatible implementation of the Gauss Rank scaling method☆74Updated 2 years ago
- ☆150Updated 2 years ago
- Feature engineering package with sklearn like functionality☆55Updated last year