Bayesian optimization in JAX

Overview

Bayesian optimization in JAX

Get started with a tutorial on Google Colab: Open Demo in Colab

To cite this repository:

@software{jaxbo2020github,
author = {Paris Perdikaris},
title = {{JAX-BO}: A Bayesian optimization library in {JAX}},
url = {https://github.com/PredictiveIntelligenceLab/JAX-BO},
version = {0.2},
year = {2020},
}
Owner
Predictive Intelligence Lab
Predictive Intelligence Lab
A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al.

pyUpSet A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al. Contents Purpose How to install How it work

288 Jan 04, 2023
PyHarmonize: Adding harmony lines to recorded melodies in Python

PyHarmonize: Adding harmony lines to recorded melodies in Python About To use this module, the user provides a wav file containing a melody, the key i

Julian Kappler 2 May 20, 2022
Timeseries analysis for neuroscience data

=================================================== Nitime: timeseries analysis for neuroscience data ===============================================

NIPY developers 212 Dec 09, 2022
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models

538 Jan 01, 2023
pure-predict: Machine learning prediction in pure Python

pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks l

Ibotta 84 Dec 29, 2022
Machine Learning for Time-Series with Python.Published by Packt

Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am

Packt 124 Dec 28, 2022
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

Tamas Madl 482 Nov 19, 2022
Machine Learning from Scratch

Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin

ShawnWang 0 Jul 05, 2022
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Real-time water systems lab 416 Jan 06, 2023
A high performance and generic framework for distributed DNN training

BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith

Bytedance Inc. 3.3k Dec 28, 2022
πŸŽ› Distributed machine learning made simple.

πŸŽ› lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started β€’ Highlight

Machine Learning Tooling 44 Nov 27, 2022
Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Artsem Zhyvalkouski 64 Nov 30, 2022
Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.

Priyansh Sharma 7 Nov 09, 2022
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

Daniel Formoso 5.7k Dec 30, 2022
Relevance Vector Machine implementation using the scikit-learn API.

scikit-rvm scikit-rvm is a Python module implementing the Relevance Vector Machine (RVM) machine learning technique using the scikit-learn API. Quicks

James Ritchie 204 Nov 18, 2022
Probabilistic time series modeling in Python

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

Amazon Web Services - Labs 3.3k Jan 03, 2023
ML Kaggle Titanic Problem using LogisticRegrission

-ML-Kaggle-Titanic-Problem-using-LogisticRegrission here you will find the solution for the titanic problem on kaggle with comments and step by step c

Mahmoud Nasser Abdulhamed 3 Oct 23, 2022
Python package for stacking (machine learning technique)

vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa

Igor Ivanov 671 Dec 25, 2022
Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Amplo 10 May 15, 2022
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here

uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain

B DEVA DEEKSHITH 1 Nov 03, 2021