Python Optimization-algorithms Resources

early-ML Presentation General Machine Learning tutorials A Python step-by-step primer for Machine Learning and Optimization This github repository gat

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

music-recommender-rest-api A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework How it works T

Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s

DP-JOA Join optimization is the process of optimizing the joining, or combining, of two or more tables in a database. Here is a simple join optimizati

Problems and it's solutions. Problem solving, a great Speed comes with a good Accuracy. The more Accurate you can write code, the more Speed you will

Differential_Privacy_CPS Python implementation of the research paper Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms Re

iAWE is a wonderful dataset for those of us who work on Non-Intrusive Load Monitoring (NILM) algorithms. You can find its main page and description via this link. If you are familiar with NILM-TK API, you probably know that you can work with iAWE hdf5 data file in NILM-TK.

Racing Line Optimization with PSO This repository contains a racing line optimization algorithm in python that uses Particle Swarm Optimization. Requi

A place to post ideas, partial projects, or anything else that doesn't necessarily warrant its own repo, from my mind to the web.

Visualization of numerical optimization algorithms

CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation

orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect

HashDB HashDB is a community-sourced library of hashing algorithms used in malware. How To Use HashDB HashDB can be used as a stand alone hashing libr

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

HDBSCAN HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.

FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu

GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl

Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen

Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our

Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

CVXPY The CVXPY documentation is at cvxpy.org. We are building a CVXPY community on Discord. Join the conversation! For issues and long-form discussio

Evol is clear dsl for composable evolutionary algorithms that optimised for joy. Installation We currently support python3.6 and python3.7 and you can

Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati

blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e

Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software

BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

gqueue gqueue is a CLI (command line interface) tool that computes carbon footprint of HPC computations on clusters running slurm. It follows the meth

TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De

Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik

GOAT A paper using optimal transport to solve the graph matching problem. https://arxiv.org/abs/2111.05366 Repo structure .github: Files specifying ho

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

My Dynamic Programming Algorithms giraycoskun [email protected] It is a repo for various dynamic programming algorithms for exercise.

Distribution System Model Calibration Algorithms The code in this library was developed by Sandia National Laboratories under funding provided by the

ProsePainter Create images by painting with words. ProsePainter combines direct digital painting with real-time guided machine-learning based image op

Multi-objective constrained optimization for energy applications via tree ensembles

Explaining Hyperparameter Optimization via PDPs This repository gives access to an implementation of the methods presented in the paper submission “Ex

Safe Policy Optimization with Local Feature (SPO-LF) This is the source-code for implementing the algorithms in the paper "Safe Policy Optimization wi

Safe Policy Optimization with Local Feature (SPO-LF) This is the source-code for implementing the algorithms in the paper "Safe Policy Optimization wi

Parameterising Simulated Annealing for the Travelling Salesman Problem

Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey Will appear on Thirty-fifth Conference on Neural Information Processing Syste

UAV-Networks Simulator - Autonomous Networking - A.A. 20/21 UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac pr

Parameterising Simulated Annealing for the Travelling Salesman Problem Abstract The Travelling Salesman Problem is a well known NP-Hard problem. Given

HPOflow - Sphinx DOC Tools for Optuna, MLflow and the integration of both. Detailed documentation with examples can be found here: Sphinx DOC Table of

Deep Learning Algorithms for Hedging with Frictions This repository contains the Forward-Backward Stochastic Differential Equation (FBSDE) solver and

PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization (CVPR 2021) This is the official implementation of PW

batch-bandits Implementation of popular bandit algorithms in batch environments. Source code to our paper "The Impact of Batch Learning in Stochastic

2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

Lightweight Hyperparameter Optimization 🚀 The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machin

Association Rules Mining Using Python Implementation of association rules mining algorithms (Apriori|FPGrowth) using python. As a part of hw1 code in

duality Data science, Data manipulation and Machine learning package. Use permitted according to the terms of use and conditions set by the attached l

scikit-multimodallearn is a Python package implementing algorithms multimodal data. It is compatible with scikit-learn, a popul

Update July 10, 2021: This repository now supports an additional symbolic optimization task: learning symbolic policies for reinforcement learning. Th

Generalized Proximal Policy Optimization with Sample Reuse This repository is the official implementation of the reinforcement learning algorithm Gene

PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i

OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio

This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a

bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im

Planning Algorithms in AI and Robotics course T2 2021-22 The Planning Algorithms in AI and Robotics course at Skoltech, MS in Data Science, during T2,

Min-Max Adversarial Attacks [Paper] [arXiv] [Video] [Slide] Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zha

Bioinformatics This is a repository of all the algorithms covered in the Bioinformatics Course part of the Cambridge Computer Science Tripos Algorithm

ROSEFusion 🌹 This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Moti

PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap

A large-scale database for graph representation learning

LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query

dbv Decision Border Visualizer for Classification Algorithms Project description A python package for Machine Learning Engineers who want to visualize

Programming-Foundations-Algorithms Algorithms purpose to solve a specific proplem with a sequential sets of steps for instance : if you need to add di

Visualize sorting algorithms A simple python application to visualize sorting algorithms. Sort Algorithms Name Function Name O( ) Bubble Sort bubble_s

🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥

Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper “Lear

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization.

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.

Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati

This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiments and research on learning to rank with human annotated or noisy labels.

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

This repository contains the Matlab implementations for the following multi-target filtering/tracking algorithms: - Folder PMBM contains the implemen

Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th

Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making Created by Iago Pachêco Gomes at USP - ICM

Data Structure and Algorithm : Want to learn data strutrues and algorithms ??? Then Stop thinking more and start to learn today. This repo will help y

RoMA: Robust Model Adaptation for Offline Model-based Optimization Implementation of RoMA: Robust Model Adaptation for Offline Model-based Optimizatio

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

toy_gradlogp This repo implements some toy examples of the following score matching algorithms in PyTorch: ssm-vr: sliced score matching with variance

IQNAS: Interpretable Integer Quadratic programming Neural Architecture Search Realistic use of neural networks often requires adhering to multiple con

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

Auto-Baby-Cry-Detection-with-Music-Player A simple voice detection system which can be applied practically for designing a device with capability to d

CodingSimplified_GK This repository is aimed at creating a One stop Destination of codes of all Data structures and Algorithms along with basic explai

Trajectory optimization package for Mini-Pupper robot Purpose of this repository is to provide low-torque and low-impact trajectory for Mini-Pupper qu

TesohhCrypt TesohhCrypt is a zero-dependency Cryptography Python Module, with a method that i made. (likely someone already made a similar one, but i