Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K…

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Bayesian optimisation & Reinforcement Learning library developped by Huawei Noah's Ark Lab

Python library for Multi-Armed Bandits

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

An Intuitive Tutorial to Gaussian Processes Regression

🔬 Research Framework for Single and Multi-Players 🎰 Multi-Arms Bandits (MAB) Algorithms, implementing all the state-of-the-art algorithms for single-player (UCB, KL-UCB, Thompson...) and multi-play…

Python code for bayesian optimization using Gaussian processes

[NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题

https://cs330.stanford.edu/

Code repo for "Function-Space Distributions over Kernels"

Resources and environment for unsupervised outlier model selection (UOMS)

The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization

A framework for QuickTune

A Multi-objective Multi-fidelity acquisition function for Bayesian optimization based on EHVI method.

Some basic utility functions for data science and data analysis

Experimental evaluation of the Oboe system.

Robust and conjugate Gaussian process

EE 761 course project: Hyperparameter tuning using Multi Armed bandits, Autumn 2019, IIT Bombay