talperetz / awesome-gradient-boosting
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:
- Part of our solution to PLAsTiCC Kaggle challenge☆18Updated 6 years ago
- A python script for a PyTorch feed forward neural network for tabular data using categorical embeddings.☆67Updated 5 years ago
- Python utilities for Machine Learning competitions☆32Updated 7 years ago
- 57th place solution in "Bosch Production Line Performance"☆19Updated 7 years ago
- TensorFlow 2.0 + Keras guide by François Chollet for deep learning researchers.☆15Updated 5 years ago
- High level utility functions for using Rapids on Kaggle Competitions☆28Updated 5 years ago
- Using Kafka-Python to illustrate a ML production pipeline☆110Updated 2 years ago
- Recruit Restaurant Visitor Forecasting 25th place solution☆12Updated 7 years ago
- General Interpretability Package☆58Updated 2 years ago
- Repository for medium article☆22Updated last year
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 2 years ago
- The 18th Place Solution to Avito Demand Prediction Challenge☆26Updated 5 years ago
- My presentation at ODSC India 2018 about Deep Learning with Apache Spark☆27Updated 6 years ago
- ☆17Updated 4 years ago
- Recency, Frequency, and Monetary are three behavioral attributes and are quite simple, in that they can be easily computed for any databa…☆15Updated last year
- Follow the Lumiata Tech Blog on Medium!☆21Updated 2 years ago
- Movie recommendation system based on movielens dataset. Bayesian approach used to predict likely rating of the movie☆12Updated 8 years ago
- ☆19Updated 4 years ago
- Tutorial for a new versioning Machine Learning pipeline☆80Updated 3 years ago
- Baseline Python Scripts for Popular Kaggle Competitions☆17Updated 2 years ago
- Preparing continuous features for neural networks with GaussRank☆45Updated 7 years ago
- Scripts for paper "Encoding high-cardinality string categorical variables"☆24Updated 5 years ago
- ☆43Updated 6 years ago
- Jupyter Notebooks for Strata Data Conference NY 2017 Deep Learning for Recommender Systems Tutorial☆22Updated 7 years ago
- ☆23Updated last year
- Variational deep autoencoder to predict churn customer☆29Updated 7 years ago
- Embed categorical variables via neural networks.☆59Updated 2 years ago
- ☆21Updated 2 years ago
- Experimental library for sampling and validating scikit-learn parameters☆10Updated 6 years ago
- 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