61 skills found · Page 1 of 3
zilliztech / VectorDBBenchBenchmark for vector databases.
similarweb / FinalaFinala is an open-source resource cloud scanner that analyzes, discloses, presents and notifies about wasteful and unused resources.
keikoproj / Minion ManagerIntelligent use of Spot Instances in Kubernetes
giabaio / BCEABayesian Cost Effectiveness Analysis. Given the results of a Bayesian model (possibly based on MCMC) in the form of simulations from the posterior distributions of suitable variables of costs and clinical benefits for two or more interventions, produces a health economic evaluation. Compares one of the interventions (the "reference") to the others ("comparators"). Produces many summary and plots to analyse the results
MichaelBeechan / ThunderNet ReviewReal-time generic object detection on mobile platforms is a crucial but challenging computer vision task. However, previous CNN-based detectors suffer from enormous computational cost, which hinders them from real-time inference in computation-constrained scenarios. In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight twostage detector named ThunderNet. In the backbone part, we analyze the drawbacks in previous lightweight backbones and present a lightweight backbone designed for object detection. In the detection part, we exploit an extremely efficient RPN and detection head design. To generate more discriminative feature representation, we design two efficient architecture blocks, Context Enhancement Module and Spatial Attention Module. At last, we investigate the balance between the input resolution, the backbone, and the detection head. Compared with lightweight one-stage detectors, ThunderNet achieves superior performance with only 40% of the computational cost on PASCAL VOC and COCO benchmarks. Without bells and whistles, our model runs at 24.1 fps on an ARM-based device. To the best of our knowledge, this is the first real-time detector reported on ARM platforms. Code will be released for paper reproduction.
hesim-dev / RceaCourse materials for learning how to perform applied cost-effectiveness analysis with R
PolicyAnalysisInc / HeRoModAn R package for running cost-effectiveness models in R. Forked from the heemod package.
gabboraron / Nvidia Disaster Risk Monitoring Using Satellite ImageryLearn how to build and deploy a deep learning model to automate the detection of flood events using satellite imagery. This workflow can be applied to lower the cost, improve the efficiency, and significantly enhance the effectiveness of various natural disaster management use cases.
Health-Economics-in-R / CEdecisiontree:deciduous_tree::deciduous_tree: Lightweight cost-effectiveness analysis using decision trees.
Bogdasayen / DOACs AF Economic ModelR code for cost-effectiveness model evaluating directly acting oral anticoagulants (DOACs) for prevention of stroke in atrial fibrillation.
Health-Economics-in-R / QALY:green_heart: :yellow_heart: :heart: An R package to calculate time-dependent person cost and health functions e.g. quality-adjusted life-years with discounting.
Merck / Psm3mkvpsm3mkv: A package to evaluate the fit and efficiency of three state oncology cost-effectiveness model structures
Roche / Global HTA Evidence OpenCollection of R Packages that support analysis for the purposes of Health Technology Assessment (HTA)
AgiFlow / Claude InstrumentEvaluate the cost-effectiveness of Claude subscription plans compared to pay-as-you-go API usage
filippolmt / Terraform Oci Free TierTerraform configurations for deploying and managing resources on Oracle Cloud Infrastructure (OCI) Free Tier. Ideal for learning, development, and small-scale projects. Features include automated deployment, cost-effectiveness, modularity, and integrated security practices.
PanduDcau / Lung Cancer ProjectThe effectiveness of cancer prediction system helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status. The data is collected from the website online lung cancer prediction system .
PolicyAnalysisInc / OpenqalyReproducible cost-effectiveness modeling
shalikaprasad / Cloud Provider Selection Recommendation Using Machine LearningCloud computing (CC) has recently been receiving tremendous attention from the IT trade and educational researchers. CC leverages its distinctive services to cloud customers in a very pay-as-you-go, anytime and anyplace manner. As well as Cloud services offer dynamically scalable services on demand. Therefore, service supplying plays a key role in CC. Then, it is good opportunity for customers to find suitable and lowly cost service for their project. Specially, Customer must be able to select appropriate cloud service according to their needs and money. It is time-consuming task for consumers to collect the necessary information and analyze from all cloud service providers to make right decision. As well as it is also a highly demanding task from a computational perspective because multiple consumers who have similar requirements conduct same computations repeatedly. They provide all products you might need for moving your business to the cloud. But these product offerings differ in pricing as well as the naming of their services. Some Businessmen already may use on-premises infrastructure or think which infrastructure will use for my project. They may have more complex problems like how to choose a cloud service, which services want use and specially how many costs want to pay for monthly or yearly. Sometimes, someone already use a cloud services, they have lot of problems like more expensive, less flexibility, hard to use, overwhelming options of services, poor management of GUI and tool, complex price schema and other issues. However, they must spend more price and time as useless. Because they could not select best cloud service provider early to their business. For solving the cloud service selection problem, many researchers have proposed some approaches including multicriteria decision analysis (MCDA) and Brokerage-Based Approach. But we cannot see any machine learning prediction system for solving this issue. This system enables the user to choose from among a number of available choices. In this paper, we make a neural network with TensorFlow to service selection in CC. This system focuses on three main players in CC. There are Amazon Web Services, Microsoft Azure and Google Cloud Platform in the race for cloud services providers. I identify and synthesize several products relevant for web services in Cloud providers. There are Featured, Compute, Storage, Database, Networking, Operation, Identity & Access and Cost. As well as I focus on Small and medium-sized businesses (SMBs). Because these are most aggressive segment in cloud service. It is less-complex IT needs, fewer legacy applications and less IT support than larger enterprises. We use Support Vector Machine (SVM), Multiple linear regression (MLR) and Multiple-criteria decision analysis (MCDA). We develop efficient and flexible recommendation system for ranking cloud service providers. I prove accuracy and effectiveness of our approach through an experimental study with the real and synthetic Cloud data.
MortadhaMannai / Disaster Risk Monitoring Using Satellite Imagery And Nvidia LibrariesLearn how to build and deploy a deep learning model to automate the detection of flood events using satellite imagery. This workflow can be applied to lower the cost, improve the efficiency, and significantly enhance the effectiveness of various natural disaster management use cases.
feralaes / Cdx2ceaCDX2 biomarker testing and adjuvant therapy for stage II colon cancer: An exploratory cost-effectiveness analysis
