28 skills found
facebookexperimental / RobynRobyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
QingruZhang / AdaLoRAAdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (ICLR 2023).
jcrichard / PyrbConstrained and Unconstrained Risk Budgeting / Risk Parity Allocation in Python
AutarkLabs / Open EnterpriseA suite of apps that includes allocation, dot voting, issue curation, and other planning tools so organizations can collectively budget and design custom reward & bounty systems.
BessieChen / Coursera Advanced Algorithms And ComplexityThis course talks about networks flows which are used in more obvious applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision. It then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements, call routing in telecommunications and many others. Next discussing inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice.
Quantoria / Risk BudgetingRisk_Budgeting is a Python project that uses the risk budgeting approach for portfolio asset allocation
palitr / Budget Optimization In Ecommerce Using Market Mix ModellingTo create a market mix model for ElecKart (an e-commerce firm from Ontario, Canada) for several products categories - to observe the actual impact of various marketing variables over the past and recommend the optimal budget allocation for different marketing levers for the next year. Built several Linear Regression models like Additive, Multiplicative, Koyck & Distributive Lag to identify the important KPIs that influence the company revenue and their contributions towards the revenue. The main data set is available below:
missjaanii / Demand ForecastingDemand Forecasting is the process in which historical sales data is used to develop an estimate of an expected forecast of customer demand. To businesses, Demand Forecasting provides an estimate of the amount of goods and services that its customers will purchase in the foreseeable future. Critical business assumptions like turnover, profit margins, cash flow, capital expenditure, risk assessment and mitigation plans, capacity planning, etc. are dependent on Demand Forecasting. Demand Forecasting is the pivotal business process around which strategic and operational plans of a company are devised. Based on the Demand Forecast, strategic and long-range plans of a business like budgeting, financial planning, sales and marketing plans, capacity planning, risk assessment and mitigation plans are formulated. Short to medium term tactical plans like pre-building, make-to-stock, make-to-order, contract manufacturing, supply planning, network balancing, etc. are execution based. Demand Forecasting also facilitates important management activities like decision making, performance evaluation, judicious allocation of resources in a constrained environment and business expansion planning.
walkerning / Differentiable Sparsity Allocationdifferentiable sparsity allocation for budgeted pruning
AmauryGouverneur / Optimal Measurement Budget Allocation For Particle FilteringParticle filtering is a powerful tool for target tracking. When the budget for observations is restricted, it is necessary to reduce the measurements to a limited amount of samples carefully selected. A discrete stochastic nonlinear dynamical system is studied over a finite time horizon. Only a given number of measurements can be acquired. The problem of selecting the optimal measurement times for particle filtering is formalized as a combinatorial optimization problem. We propose an approximated solution based on the nesting of a genetic algo-rithm, a Monte Carlo algorithm and a particle filter. Firstly, an example demonstrates that the genetic algorithm outperforms a random trial optimization. Then, the interest of non-regular measurements versus measurements performed at regular time intervals is illustrated and the efficiency of our proposed solution is quantified.
CodeForAfrica / PesaYetuPesaYetu, an easy-to-use visualization tool that helps journalists quickly find, analyse and compare government budget data to help fact-check claims about resource allocations, public procurement and development plans or services. Accessible at https://pesayetu.pesacheck.org
teamforus / ForusPlatform Forus is an Open SaaS solution that facilitates the management and issuance of social benefits, offering a collaborative platform for municipalities, charities, citizens, and providers to streamline budget allocation, resource distribution, and eligibility validation.
junhongmit / P And B🧠Plan-and-Budget: Training-free test-time reasoning framework for adaptive token allocation in large language models (ICLR 2026).
Zihan-Liu-00 / NeurIPS22 GraDPyTorch Implementation for NeurIPS 2022 paper 'Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias'
smmalik98 / MMM PyMC3 MarketingMarketing Mixed Modelling using PyMC3-Marketing
buger / Budget Allocation UiNo description available
zcchenvy / MLBC DQNcode for paper 《Advertising Impression Resource Allocation Strategy with Multilevel Budget Constraint DQN in Real-Time Bidding》
vuritiaditya / Software EstimationPrediction of software development cost is an extremely important task before starting the actual development phase. Software products are acceptable by clients as long as they are developed within the lower budget. Software estimation is one of the most challenging areas of project management. Machine learning algorithms are used to handle these type of problems. Machine learning algorithms increase project success rates. software simulation using machine learning algorithms could further enhance project estimation methods and contribute to better resource allocation and utilization. The proposed effort and duration estimation models are intended to serve as a decision support tool for any organization developing and implementing software systems. ISBSG dataset is used for this implementation. Results show that machine learning models can be used to predict software cost with high accuracy rate. Keywords : ISBSG,Software project estimation,Effort and duration estimation, Prediction.
Sabermahjoub / Fin GeniusFinGenius : a python-based expert system for financial assistance and budget allocation, featuring interactive charts.
BBVA / Budget Allocation DRLNo description available
