A curated list of gradient boosting research papers with implementations.
-
Updated
Mar 16, 2024 - Python
A curated list of gradient boosting research papers with implementations.
A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python
NOTE: skutil is now deprecated. See its sister project: https://github.com/tgsmith61591/skoot. Original description: A set of scikit-learn and h2o extension classes (as well as caret classes for python). See more here: https://tgsmith61591.github.io/skutil
D2C(Data-driven Control Library) is a library for data-driven control based on reinforcement learning.
Benchmark of current ML automation frameworks
This repo contains various data science strategy and machine learning models to deal with structure as well as unstructured data. It contains module on feature-preprocessing, feature-engineering, machine-learning-models, bayesian-parameter-tuning, etc, built using libraries such as scikit-learn, keras, h2o, xgboost, lightgbm, catboost, etc.
A machine learning approach to soil moisture estimation using NASA's CYGNSS data.
Verteego Data Suite documentation
This my entry for the Titanic competition on Kaggle. May 2019: public score is 0.80382, which is a top 10% ranking on the leader board of around 11.249 participants.
Yet - Another - Auto - ML
DayF (Decision at your Fingertips) is an AutoML opensource project
Python program utilizing H2O to predict credit approval using the Naïve Bayes Classifier.
Prometheus Scraper for and Coin Analysis of crypto from coinmarketcap
It's a notification for your daily water intake with amazing water factz..
Automatically determine trends, correlations, and feature selections given dataset(s)
Utilities to use google/quic-trace with `h2olog quic` logs
Add a description, image, and links to the h2o topic page so that developers can more easily learn about it.
To associate your repository with the h2o topic, visit your repo's landing page and select "manage topics."