Apress / modern-deep-learning-tabular-dataLinks
Source Code for 'Modern Deep Learning for Tabular Data' by Andre Ye and Ziang Wang
☆31Updated 2 years ago
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
Sorting:
- A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)☆86Updated 2 years ago
- Repository for the explanation method Calibrated Explanations (CE)☆69Updated last month
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors☆48Updated 3 years ago
- A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.☆44Updated 2 months ago
- Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictiv…☆22Updated last year
- Automatic machine learning for tabular data. ⚡🔥⚡☆70Updated 3 years ago
- nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets☆68Updated 2 years ago
- ☆115Updated last year
- Official repository for the book Time Series Forecasting with Foundation Models☆23Updated last month
- Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗☆156Updated this week
- Resources for some of our education content☆42Updated 3 weeks ago
- Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications☆103Updated 2 years ago
- Causal Learning: A new ML framework utilizing cooperative networks☆3Updated 10 months ago
- A framework for calibration measurement of binary probabilistic models☆28Updated last year
- Feature engineering package with sklearn like functionality☆54Updated 10 months ago
- The Orange Book of Machine Learning☆45Updated 4 months ago
- ☆32Updated last year
- How to Interpret SHAP Analyses: A Non-Technical Guide☆56Updated 3 years ago
- Forecasting: Principles and Practice☆59Updated 3 years ago
- Main folder. Material related to my books on synthetic data and generative AI. Also contains documents blending components from several f…☆96Updated 10 months ago
- hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…☆64Updated 4 months ago
- Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.☆40Updated 6 months ago
- Experiments on Tabular Data Models☆278Updated 2 years ago
- This project introduces Causal AI and how it can drive business value.☆48Updated 10 months ago
- Package designed for handling imbalanced classification☆18Updated last year
- Code for the new Manning book on machine learning on tabular datasets☆43Updated 5 months ago
- A Living Benchmark for Machine Learning on Tabular Data☆100Updated this week
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.☆65Updated 5 months ago
- Code used to obtain results for my medium articles☆75Updated 2 years ago
- Revisiting Pretrarining Objectives for Tabular Deep Learning☆65Updated 2 years ago