Python Optimization-algorithms Resources

AutoTrader AutoTrader is Python-based platform intended to help in the development, optimisation and deployment of automated trading systems. From sim

KFAC-JAX - Second Order Optimization with Approximate Curvature in JAX Installation | Quickstart | Documentation | Examples | Citing KFAC-JAX KFAC-JAX

Best Data Science Resources Hey, Data Enthusiasts out there! Finally, after lots of requests from the community I finally came up with the best free D

NEW RELEASE How Nebullvm Works • Tutorials • Benchmarks • Installation • Get Started • Optimization Examples Discord | Website | LinkedIn | Twitter Ne

ML-ProjectKart 📌 Repository This kart showcases the finest collection of all projects based on machine learning, deep learning, computer vision, natu

👏 Pre- requisites to Machine Learning

Multi-Type-TD-TSR Check it out on Source Code of our Paper: Multi-Type-TD-TSR Extracting Tables from Document Images using a Multi-stage Pipeline for

DodgeDrone: Vision-based Agile Drone Flight (ICRA 2022 Competition) Would you like to push the boundaries of drone navigation? Then participate in the

Ana's Portfolio ✌️ Welcome to my Portfolio! You will find here different Projects I have worked on (from scratch) 💪 Projects 💻 1️⃣ Hangman game (Mad

Intrusion-Detection-System-Using-CNN-and-Transfer-Learning This is the code for the paper entitled "A Transfer Learning and Optimized CNN Based Intrus

Description This repository contains code accompanying the following paper on the Make-It robotic flow chemistry platform developed by the Jensen Rese

WIE-WoC IEEE-WIE presents WIE Week of Code (WIEWoC), a 3-days long open-source contribution event starting from 1st March, highlighting different pyth

Cooper About Cooper is a toolkit for Lagrangian-based constrained optimization in Pytorch. This library aims to encourage and facilitate the study of

30-Days-of-ML-Kaggle 🔥 About the Hands On Program 💻 Machine learning beginner → Kaggle competitor in 30 days. Non-coders welcome The program starts

AI Seed Projects Start with ready code for your next AI experiment. Choose from 1000+ code templates, across a wide variety of use cases. All examples

Billion-Scale ANN http://big-ann-benchmarks.com/ Install The only prerequisite is Python (tested with 3.6) and Docker. Works with newer versions of Py

Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

Basic Machine Learning Algorithms All the basic Machine Learning Algorithms are implemented in Python using libraries Acknowledgements Machine Learnin

Soomvaar 📌 Introduction Soomvaar is the collection of various codes implement in machine learning and machine learning algorithms with python on coll

OptiCL OptiCL is an end-to-end framework for mixed-integer optimization (MIO) with data-driven learned constraints. We address a problem setting in wh

sne4onnx A very simple tool for situations where optimization with onnx-simplifier would exceed the Protocol Buffers upper file size limit of 2GB, or

hyperbox-brain is a Python open source toolbox implementing hyperbox-based machine learning algorithms built on top of scikit-learn and is distributed

Athena Portfolio optimization is the process of selecting the best portfolio (asset distribution), out of the set of all portfolios being considered,

Overview of Credit Card Analysis In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm

EasyMCDM - Quick Installation methods Install with PyPI Once you have created your Python environment (Python 3.6+) you can simply type: pip3 install

Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M

Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M

Data Structures and Algorithms All the essential resources and template code nee

autolfads-tf2 A TensorFlow 2.0 implementation of LFADS and AutoLFADS. Installati

How does the encrypter works? Transform your text into encrypted symbols using t

event-forecasting Event Forecasting Algorithms Theory Correlating events in comp

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the

Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.

Cormen Lib Sample Problems Description This repository contnains sample problems with test cases using Cormen-Lib. These problems were made for the pu

OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.

AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin

evolvingrl Supplementary Data for Evolving Reinforcement Learning Algorithms This dataset contains 1000 loss graphs from two experiments: 500 unique g

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys in IEEE Transactions o

Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe

QDax: Accelerated Quality-Diversity QDax is a tool to accelerate Quality-Diveristy (QD) algorithms through hardware accelerators and massive paralleli

GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.

LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer

Python red-black trees A Python implementation of red-black trees. This code was originally copied from programiz.com, but I have made a few tweaks to

Nonlinear Optimization Algorithms During my time as Scientific Assistant at the Karlsruhe Institute of Technology (Germany) I implemented various Opti

CLASSIX Fast and explainable clustering based on sorting CLASSIX is a fast and explainable clustering algorithm based on sorting. Here are a few highl

Brainda Welcome! First and foremost, Welcome! Thank you for visiting the Brainda repository which was initially released at this repo and reorganized

MOEA-HH An open-source hyper-heuristic framework for multi-objective optimization. Introduction The multi-objective optimization technique is widely u

Codenames Code infrastructure and player algorithms for the Codenames board game. This is the active fork of mkali-personal/codenames. Intro This is b

Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters

Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces" This repo contains the implementation of GEBO algorithm.

Fliscopt FLIght SCheduling OPTimization 🛫 or fliscopt is a simple optimization library for flight scheduling and related problems in the discrete dom

ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn

Current gate-based quantum computers have the potential to provide a computational advantage if algorithms use quantum hardware efficiently.

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.

Crypto Portfolio Clustering Crypto Portfolio Clustering with and without optimization techniques (elbow method, PCA). Analysis This is an anlysis of c

Balabobapy - Using artificial intelligence algorithms to continue the text

Demo-of-MCMC These files are based on the class materials of AEROSP 567 taught by Prof. Alex Gorodetsky at University of Michigan. Author: Hung-Hsiang

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed model for heart failure prediction accuracy of 88 percent.

Basic sort and search algorithms written in python. These were all developed as part of my Computer Science course to demonstrate understanding so they aren't 100% efficent

Genetic algorithms are heuristic search algorithms inspired by the process that supports the evolution of life. The algorithm is designed to replicate the natural selection process to carry generation, i.e. survival of the fittest of beings.

Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme

Automating reinforcement learning architecture design for code optimization. Che

QVC Optimizer Review Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits". Each of the python files ca

RRT-Algorithm-Visualisation This is a project that aims to develop upon the RRT

CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c

Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize

Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Acceder al código desde Google Colab para poder ver de manera adecuada todas las visualizaciones y poder interactuar con ellas. Links de acceso: Noteb

LINUX-AOS (Automatic Optimization System)

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

Approximate Multiplier by HEAM What's HEAM? HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific app

ReLSO Improved Fitness Optimization Landscapes for Sequence Design Description Citation How to run Training models Original data source Description In

Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto

AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted

Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization This repository contains the code for the BBI optimizer, introduced in the p

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!

eo-grow Earth observation framework for scaled-up processing in Python. Analyzing Earth Observation (EO) data is complex and solutions often require c

Final Project for Practical Python Programming and Algorithms for Data Analysis (PHW2781L, Summer 2020) Redlining, Race-Exclusive Deed Restriction Lan

Wordle Game This is a python implementation of wordle, which uses the same set of available words as the hit game, Wordle. Play the game manually pyth

scikit-event-correlation Event Correlation and Changing Detection Algorithm Theo

A library for benchmarking, developing and deploying deep learning anomaly detection algorithms Key Features • Getting Started • Docs • License Introd

Tools for mathematical optimization region

The Cormen-lib module is an insular data structures and algorithms library based on the Thomas H. Cormen's Introduction to Algorithms Third Edition. This library was made specifically for administering and grading assignments related to data structure and algorithms in computer science.

package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor

**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map, play blackjack game and robot in grid world and evaluate reward for it

Look into Palanteer and get an omniscient view of your program Palanteer is a set of lean and efficient tools to improve the quality of software, for

Qcover is an open source effort to help exploring combinatorial optimization problems in Noisy Intermediate-scale Quantum(NISQ) processor. It is devel

100 Days of Code Learning program to keep a habit of coding daily and learn things at your own pace with help from our remote community.

Algo_Visualizer This project is an Algorithm Visualizer where a user can visualize common algorithms like "Bubble Sort", "Merge Sort", "Quick Sort", "

A computational optimization project towards the goal of gerrymandering the results of a hypothetical election in the UK.

PyGRANSO PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation Please check https://ncvx.org/PyGRANSO for detailed instructions (introd