Search Results for "metric"
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Showing 163 open source projects for "metric"
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Managing your therapy and rehab practice is a time-consuming process. You spend hours on paperwork, billing, scheduling, and more. Raintree’s Therapy & Rehab EHR is here to help you manage your practice more efficiently. With our all-in-one solution, you’ll get the tools you need to streamline your therapy and rehab practice, improve patient care, and get back to doing what you love.
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Exact Payments delivers easy-to-integrate embedded payment solutions enabling you to rapidly onboard merchants, instantly activate a variety of payment methods and accelerate your revenue — delivering an end-to-end payment processing platform for SaaS businesses.
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1
TorchMetrics
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 80+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. The module-based metrics contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices! Automatic accumulation over multiple batches. Automatic... -
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Metrics
Capturing JVM and application-level metrics
... functionality. The starting point for Metrics is the MetricRegistry class, which is a collection of all the metrics for your application (or a subset of your application). Each metric is associated with a MetricRegistry, and has a unique name within that registry. A gauge is the simplest metric type. It just returns a value. If, for example, your application has a value which is maintained by a third-party library, you can easily expose it by registering a Gauge instance which returns that value. -
3
Thanos
Highly available Prometheus setup with long term storage capabilities
... speedup when querying large time ranges or configure complex retention policies. Thanos leverages the Prometheus 2.0 storage format to cost-efficiently store historical metric data in any object storage while retaining fast query latencies. Additionally, it provides a global query view across all Prometheus installations and can merge data from Prometheus HA pairs on the fly. -
4
dive
A tool for exploring each layer in a docker image
.... The lower left pane shows basic layer info and an experimental metric that will guess how much wasted space your image contains. This might be from duplicating files across layers, moving files across layers, or not fully removing files. Both a percentage "score" and total wasted file space is provided. You can build a Docker image and do an immediate analysis with one command: dive build -t some-tag . -
Our robust pre-built connectors and our no-code, drag-and-drop interface makes it easy and fast to automatically sync vendors, invoices, and invoice payment data between Tipalti and your ERP or accounting software.
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle... -
6
JMX Exporter
A process for exposing JMX Beans via HTTP for Prometheus consumption
JMX to Prometheus exporter: a collector that can configurable scrape and expose mBeans of a JMX target. This exporter is intended to be run as a Java Agent, exposing a HTTP server and serving metrics of the local JVM. It can be also run as a standalone HTTP server and scrape remote JMX targets, but this has various disadvantages, such as being harder to configure and being unable to expose process metrics (e.g., memory and CPU usage). Running the exporter as a Java agent is strongly... -
7
smclarify
Fairness aware machine learning. Bias detection and mitigation
... that returns a bias metric. A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure. A collection of bias metrics for a given dataset or a combination of a dataset and model. -
8
wego
Weather app for the terminal
... variable to override the default config file location. Displayed info (metric or imperial units), temperature range (felt and measured), windspeed and direction, viewing distance, precipitation amount and probability. -
9
Ludwig AI
Low-code framework for building custom LLMs, neural networks
...), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning. -
Give your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
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10
Argo Rollouts
Progressive Delivery for Kubernetes
Argo Rollouts is a Kubernetes controller and set of CRDs that provide advanced deployment capabilities such as blue-green, canary, canary analysis, experimentation, and progressive delivery features to Kubernetes. Argo Rollouts (optionally) integrates with ingress controllers and service meshes, leveraging their traffic shaping abilities to gradually shift traffic to the new version during an update. Additionally, Rollouts can query and interpret metrics from various providers to verify key... -
11
Evaluate
A library for easily evaluating machine learning models and datasets
Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized. -
12
Micrometer Application Metrics
App observability facade for the most popular observability tools
Micrometer provides a simple facade over the instrumentation clients for the most popular observability systems, allowing you to instrument your JVM-based application code without vendor lock-in. Think SLF4J, but for observability. Micrometer provides vendor-neutral interfaces for timers, gauges, counters, distribution summaries, and long task timers with a dimensional data model that, when paired with a dimensional monitoring system, allows for efficient access to a particular named metric... -
13
PML
The easiest way to use deep metric learning in your application
This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you... -
14
BERTScore
BERT score for text generation
Automatic Evaluation Metric described in the paper BERTScore: Evaluating Text Generation with BERT (ICLR 2020). We now support about 130 models (see this spreadsheet for their correlations with human evaluation). Currently, the best model is Microsoft/debate-large-online, please consider using it instead of the default roberta-large in order to have the best correlation with human evaluation. -
15
flagger
Progressive delivery Kubernetes operator (Canary, A/B Testing)
Flagger is a progressive delivery tool that automates the release process for applications running on Kubernetes. It reduces the risk of introducing a new software version in production by gradually shifting traffic to the new version while measuring metrics and running conformance tests. Flagger implements several deployment strategies (Canary releases, A/B testing, Blue/Green mirroring) using a service mesh (App Mesh, Istio, Linkerd, Kuma, Open Service Mesh) or an ingress controller... -
16
Gocache
Go cache library that brings you multiple ways to manage caches
Guess what is Gocache? a Go cache library. This is an extendable cache library that brings you a lot of features for caching data. Multiple cache stores: actually in memory, redis, or your own custom store. A chain cache: use multiple cache with a priority order (memory then fallback to a redis shared cache for instance) A loadable cache: allow you to call a callback function to put your data back in cache. A metric cache to let you store metrics about your caches usage (hits, miss, set success... -
17
Sysdig Inspect
A powerful opensource interface for container troubleshooting
Sysdig Inspect is a powerful opensource interface for container troubleshooting and security investigation. Inspect's user interface is designed to intuitively navigate the data-dense sysdig captures that contain granular system, network, and application activity of a Linux system. Sysdig Inspect helps you understand trends, correlate metrics and find the needle in the haystack. It comes packed with features designed to support both performance and security investigations, with deep... -
18
EvoTrees.jl
Boosted trees in Julia
A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood. -
19
Backpex
Backpex is a highly customizable administration panel for Phoenix Live
... resources for a quick glance at your date. More metric types are in the making. -
20
UMAP
Uniform Manifold Approximation and Projection
Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction. It is possible to model the manifold with a fuzzy topological structure. The embedding is found by searching for a low-dimensional projection of the data that has the closest possible equivalent fuzzy topological structure. First of all UMAP is fast. It can handle large datasets and high dimensional... -
21
ParallelStencil.jl
Package for writing high-level code for parallel stencil computations
... implementation; in absolute terms, it reached 70% of the theoretical upper performance bound of the used Nvidia P100 GPU, as defined by the effective throughput metric, T_eff. ParallelStencil relies on the native kernel programming capabilities of CUDA.jl and AMDGPU.jl and on Base.Threads for high-performance computations on GPUs and CPUs, respectively. It is seamlessly interoperable with ImplicitGlobalGrid.jl, which renders the distributed parallelization of stencil-based GPU and CPU apps. -
22
Prometheus JVM Client
Prometheus instrumentation library for JVM applications
It supports Java, Clojure, Scala, JRuby, and anything else that runs on the JVM. If you use Maven, you can simply reference the assets below. The latest version can be found on in the maven repository for io.prometheus. By default, counters, histograms, and summaries export an additional series suffixed with _created and a value of the unix timestamp for when the metric was created. Building the repository needs Java 11 (The project the project still supports Java 6 and Java versions > 11... -
23
Segmentation Models
Segmentation models with pretrained backbones. PyTorch
... results (higher metric score and faster convergence). It is not necessary in case you train the whole model, not only the decoder. Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported. Input channels parameter allows you to create models, which process tensors with an arbitrary number of channels. -
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LinDB
LinDB is a scalable, high performance, high availability database
LinDB is a scalable, high-performance, high-availability distributed time series database. A single server could easily support more than one million write TPS; With fundamental techniques like efficient compression storage and parallel computing, LinDB delivers highly optimized query performance. The multi-channel replication protocol supports any amount of nodes, and ensures the system's availability. Schema-free multi-dimensional data model with Metric, Tags, and Fields; The LinQL... -
25
Popeye
A Kubernetes cluster resource sanitizer
... a metric-server, it reports potential resources over/under allocations and attempts to warn you should your cluster run out of capacity. Popeye is a readonly tool, it does not alter any of your Kubernetes resources in any way! Popeye is not another static analysis tool. It runs and inspect Kubernetes resources on live clusters and sanitize resources as they are in the wild!