jianzhnie / AutoTabularLinks
Automatic machine learning for tabular data. ⚡🔥⚡
☆70Updated 4 years ago
Alternatives and similar repositories for AutoTabular
Users that are interested in AutoTabular are comparing it to the libraries listed below
Sorting:
- A neural network hyper parameter tuner☆30Updated 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
- CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system☆76Updated 3 years ago
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.☆65Updated last year
- A toolkit to boost the productivity of machine learning engineers.☆52Updated 3 years ago
- Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production…☆29Updated 2 years ago
- ForML - A development framework and MLOps platform for the lifecycle management of data science projects☆107Updated 2 years ago
- Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.☆51Updated 2 years ago
- Revisiting Pretrarining Objectives for Tabular Deep Learning☆66Updated 3 years ago
- FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)☆72Updated 4 years ago
- Benchmark tabular Deep Learning models against each other and other non-DL techniques☆57Updated 4 years ago
- hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…☆65Updated 3 weeks ago
- Fast Differentiable Forest lib with the advantages of both decision trees and neural networks☆78Updated 4 years ago
- Automated Tool for Optimized Modelling☆163Updated last year
- Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟☆52Updated 4 years ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆92Updated 2 years ago
- Boosted neural network for tabular data☆217Updated last year
- ☆64Updated 2 years ago
- Synthetic Data Generation for mixed-type, multivariate time series.☆120Updated this week
- [AMAI 2024] Selective: Feature Selection Library☆69Updated 5 months ago
- Time-Series Cross-Validation Module☆47Updated 4 years ago
- machine learning model performance metrics & charts with confidence intervals, optimized with numba to be fast☆16Updated 4 years ago
- This repository accompanies the paper "Learning Concept Embeddings from Temporal Data" (Meyer, Van Der Merwe, and Coetsee, 2018)☆60Updated 7 years ago
- Best practices for engineering ML pipelines.☆36Updated 3 years ago
- Various methods for generating synthetic data for data science and ML☆82Updated 4 years ago
- Random Forest or XGBoost? It is Time to Explore LCE☆70Updated 2 years ago
- The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).☆223Updated last month
- Modification of TabNet as suggested in the Medium article, "The Unreasonable Ineffectiveness of Deep Learning on Tabular Data"☆62Updated 2 years ago
- Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.☆42Updated 2 years ago
- Code for the anonymous submission "Cockpit: A Practical Debugging Tool for Training Deep Neural Networks"☆31Updated 5 years ago