Python Cost-optimization Resources

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

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

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

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

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

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

Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost LOVE is accpeted by ACL22 main conference as a long pape

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

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

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

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

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

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

distance sensor cube timer A rubiks cube timer using a distance sensor and a raspberry pi 4, and possibly the pi pico to reduce size and cost. How to

Zero-Cost-NAS Companion code for the ICLR2021 paper: Zero-Cost Proxies for Lightweight NAS tl;dr A single minibatch of data is used to score neural ne

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

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

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

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.

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

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

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

LINUX-AOS (Automatic Optimization System)

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

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

Tools for mathematical optimization region

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.

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

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

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

SAPE Project page Paper Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization". Environment Cre

PEPit: Performance Estimation in Python This open source Python library provides a generic way to use PEP framework in Python. Performance estimation

Optimization-Planning-for-3D-ConvNets Code for the ICML 2021 paper: Optimization Planning for 3D ConvNets. Authors: Zhaofan Qiu, Ting Yao, Chong-Wah N

Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp

Computational Design and Dynamics of Soft Systems · This is a repository that contains the source code for generating the lecture notes, handouts, exe

End-To-End Optimization of LiDAR Beam Configuration arXiv | IEEE Xplore This repository is the official implementation of the paper: End-To-End Optimi

Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.

Privacy-focused, free, open-source cryptocurrency US tax calculator, up to date for 2021: it handles multiple coins/exchanges and computes long/short-term capital gains, cost bases, in/out lot relationships, and account balances. It supports FIFO and LIFO and it generates output in form 8949 format. It has a programmable plugin architecture.

Designed a greedy algorithm based on Markov sequential decision-making process in MATLAB/Python to optimize using Gurobi solver, the wheel size, gear shifting sequence by modeling drivetrain constraints to achieve maximum laps in a race with a 2-hour time window.

PyPortfolioOpt has recently been published in the Journal of Open Source Software 🎉 PyPortfolioOpt is a library that implements portfolio optimizatio

GPOEO GPOEO is a micro-intrusive GPU online energy optimization framework for iterative applications. We also implement ODPP [1] as a comparison. [1]

Last updated 2020/04/19 Low-Cost Open-Source Ventilator-ish Device or PAPR NOTE: This is currently an independent project not affiliated with any comm

Medical Appointments No-shows Why do 20% of patients miss their scheduled appointments? A person makes a doctor appointment, receives all the instruct

Advisor Introduction Advisor is the hyper parameters tuning system for black box optimization. It is the open-source implementation of Google Vizier w

Welcome to DCA Stack! An Automated Dollar Cost Averaging Bot For Your Crypto Web

deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen

Machine Learning in Asset Management If you like this type of content then visit ML Quant site below: https://www.ml-quant.com/ Part One Follow this l

Design-Bench Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box

EMTAUC We provided a matlab implementation for an evolutionary multitasking AUC optimization framework (EMTAUC). In this code, SBGA is considered a ba

Data-Scrapping SEO - the project uses various data scrapping and Google autocompletes API tools to provide relevant points of different keywords so that search engines can be optimized; as this information is gathered, the marketing team can target the top keywords to get your company’s website higher on a results page.

AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

Medical-Insurance-Cost-Prediction-using-Machine-learning - Here in this project, I will use regression analysis to predict medical insurance cost for people in different regions, and based on several aspects like : Smoking, Number of children, BMI...etc.

Optimizers Visualized Visualization of how different optimizers handle mathematical functions for optimization. Contents Installation Usage Functions

Scale complex AI/ML pipelines anywhere CodeFlare is a framework to simplify the integration, scaling and acceleration of complex multi-step analytics

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different

################################################################################### #

pycsminwel This is a locol minimization algorithm. Uses a quasi-Newton method with BFGS update of the estimated inverse hessian. It is robust against

MADGRAD Optimization Method A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization pip install madgrad Try it out! A best

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

Flyable - A python compiler for highly performant code Flyable is a Python compiler that generates efficient native code. It uses different techniques

Semantic correspondence Few-shot segmentation Cost Aggregation Is All You Need for Few-Shot Segmentation For more information, check out project [Proj

ChipSHOUTER-PicoEMP The PicoEMP is a low-cost Electromagnetic Fault Injection (EMFI) tool, designed specifically for self-study and hobbiest research.

Python HPC Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámb

Curriculum Dropout Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability dis

O S L O Open Source framework for Large-scale transformer Optimization What's New: December 21, 2021 Released OSLO 1.0. What is OSLO about? OSLO is a

PPOPT Python Parametric OPtimization Toolbox (PPOPT) is a software platform for solving and manipulating multiparametric programs in Python. This pack

CFMM Optimal Routing This repository contains the code needed to generate the figures used in the paper Optimal Routing for Constant Function Market M

pybnb A parallel branch-and-bound engine for Python. This software is copyright (c) by Gabriel A. Hackebeil (gabe.hacke

STORM Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit [Install Instructions] [Paper] [Website] This package contains code

AdversarialTexture Adversarial Texture Optimization from RGB-D Scans (CVPR 2020). Scanning Data Download Please refer to data directory for details. B

Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ

The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

COSCO Framework COSCO is an AI based coupled-simulation and container orchestration framework for integrated Edge, Fog and Cloud Computing Environment

Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.

PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear

NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here: