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
☆48Updated 5 months ago
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☆92Updated 2 years ago
- PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in…☆139Updated 11 months ago
- ☆203Updated 3 months ago
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆159Updated 3 years ago
- ☆17Updated 3 years ago
- Kaggle Pipeline for tabular data competitions☆205Updated last year
- Applied Machine Learning Explainability Techniques, published by Packt☆247Updated last month
- ☆53Updated 3 years ago
- TabNet for fastai☆124Updated 4 months ago
- ☆150Updated 2 months ago
- Codebase for the blog post "24 Evaluation Metrics for Binary Classification (And When to Use Them)"☆56Updated 6 years ago
- xverse (XuniVerse) is collection of transformers for feature engineering and feature selection☆117Updated 2 years ago
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆583Updated last year
- Applied Machine Learning with Python☆80Updated last year
- zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range fr…☆251Updated 3 weeks ago
- Winning Solution of Kaggle Mechanisms of Action (MoA) Prediction.☆123Updated 3 years ago
- A general purpose recommender metrics library for fair evaluation.☆277Updated 2 years ago
- References to the Medium articles☆86Updated 3 years ago
- Boosted neural network for tabular data☆217Updated last year
- Example usage of scikit-hts☆57Updated 3 years ago
- SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.☆153Updated 9 months ago
- Python package for Imputation Methods☆251Updated 2 years ago
- A Tensorflow 2.0 implementation of TabNet.☆245Updated 2 years ago
- NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for …☆108Updated 3 years ago
- Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.☆42Updated 2 years ago
- Example machine learning pipeline with MLflow and Hydra☆95Updated 2 years ago
- Data Science Feature Engineering and Selection Tutorials☆290Updated 2 weeks ago
- A power-full Shapley feature selection method.☆213Updated 3 months ago
- Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networks☆25Updated 6 years ago
- Fast SHAP value computation for interpreting tree-based models☆553Updated 2 years ago