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 collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Chris Santiago 0 Mar 30, 2022
Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared

Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset

kemalgunay 5 Apr 21, 2022
A concept I came up which ditches the idea of "layers" in a neural network.

Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl

Anik Patel 4 Dec 05, 2021
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
虚拟货币(BTC、ETH)炒币量化系统项目。在一版本的基础上加入了趋势判断

🎉 第二版本 🎉 (现货趋势网格) 介绍 在第一版本的基础上 趋势判断,不在固定点位开单,选择更优的开仓点位 优势: 🎉 简单易上手 安全(不用将api_secret告诉他人) 如何启动 修改app目录下的authorization文件

幸福村的码农 250 Jan 07, 2023
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data

MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use

Pachter Lab 26 Nov 29, 2022
dirty_cat is a Python module for machine-learning on dirty categorical variables.

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

637 Dec 29, 2022
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

3 Apr 10, 2022
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

2 Jun 14, 2022
Bonsai: Gradient Boosted Trees + Bayesian Optimization

Bonsai is a wrapper for the XGBoost and Catboost model training pipelines that leverages Bayesian optimization for computationally efficient hyperparameter tuning.

24 Oct 27, 2022
Implementation of K-Nearest Neighbors Algorithm Using PySpark

KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https:

Zachary Petroff 4 Dec 30, 2022
Factorization machines in python

Factorization Machines in Python This is a python implementation of Factorization Machines [1]. This uses stochastic gradient descent with adaptive re

Corey Lynch 892 Jan 03, 2023
Esse é o meu primeiro repo tratando de fim a fim, uma pipeline de dados abertos do governo brasileiro relacionado a compras de contrato e cronogramas anuais com spark, em pyspark e SQL!

Olá! Esse é o meu primeiro repo tratando de fim a fim, uma pipeline de dados abertos do governo brasileiro relacionado a compras de contrato e cronogr

Henrique de Paula 10 Apr 04, 2022
Titanic Traveller Survivability Prediction

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

John Phillip 0 Jan 20, 2022
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow

SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference S

OptaPy 208 Dec 27, 2022
A modular active learning framework for Python

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

modAL 1.9k Dec 31, 2022
A logistic regression model for health insurance purchasing prediction

Logistic_Regression_Model A logistic regression model for health insurance purchasing prediction This code is using these packages, so please make sur

ShawnWang 1 Nov 29, 2021
Winning solution for the Galaxy Challenge on Kaggle

Winning solution for the Galaxy Challenge on Kaggle

Sander Dieleman 483 Jan 02, 2023
Apache Liminal is an end-to-end platform for data engineers & scientists, allowing them to build, train and deploy machine learning models in a robust and agile way

Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validat

The Apache Software Foundation 121 Dec 28, 2022