talperetz / awesome-gradient-boostingLinks
A curated list of Gradient Boosting resources for Data Scientists
☆16Updated 6 years ago
Alternatives and similar repositories for awesome-gradient-boosting
Users that are interested in awesome-gradient-boosting are comparing it to the libraries listed below
Sorting:
- A python script for a PyTorch feed forward neural network for tabular data using categorical embeddings.☆67Updated 5 years ago
- Using Kafka-Python to illustrate a ML production pipeline☆112Updated 2 years ago
- General Interpretability Package☆58Updated 2 years ago
- xverse (XuniVerse) is collection of transformers for feature engineering and feature selection☆118Updated 2 years ago
- Python utilities for Machine Learning competitions☆32Updated 7 years ago
- Sample data science projects (machine learning, optimization, business intelligence)☆28Updated 6 years ago
- No Regrets: A deep dive comparison of bandits and A/B testing☆47Updated 7 years ago
- High level utility functions for using Rapids on Kaggle Competitions☆28Updated 5 years ago
- A tour through recommendation algorithms in python [IN PROGRESS]☆177Updated 6 months ago
- Measure and visualize machine learning model performance without the usual boilerplate.☆97Updated 10 months ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 2 years ago
- Train multi-task image, text, or ensemble (image + text) models☆45Updated last year
- Part of our solution to PLAsTiCC Kaggle challenge☆18Updated 6 years ago
- Library for Multi-objective optimization in Gradient Boosted Trees☆77Updated 10 months ago
- ☆27Updated 3 years ago
- Embed categorical variables via neural networks.☆59Updated 2 years ago
- Guide for applying Unit Testing in data-driven projects☆19Updated 5 years ago
- Jupyter Notebooks for Strata Data Conference NY 2017 Deep Learning for Recommender Systems Tutorial☆22Updated 7 years ago
- Training time estimation for scikit-learn algorithms☆124Updated 4 years ago
- Workshop on Target Leakage in Machine Learning I taught at ODSC Europe 2018 (London) and ODSC East 2019, 2020 (Boston)☆37Updated 5 years ago
- Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deploym…☆62Updated 2 years ago
- The deepr module provide abstractions (layers, readers, prepro, metrics, config) to help build tensorflow models on top of tf estimators☆52Updated last year
- A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.☆102Updated 3 years ago
- Winning Solution to the Kaggle Days Paris offline competition☆63Updated 6 years ago
- TSFresh primitives for featuretools☆36Updated 2 years ago
- Run any Jupyter notebook instantly using Kaggle kernels☆63Updated 5 years ago
- Finding customer lookalikes using Machine Learning in PySpark☆33Updated 6 years ago
- Using Imblearn To Tackle Imbalanced Data Sets☆37Updated 8 years ago
- Kaggle Days Paris - Competitive GBDT Specification and Optimization Workshop☆92Updated 2 years ago
- [Intemarché] Sales forecasting challenge☆11Updated 4 years ago