Search Results for "java-ml" - Page 11
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Showing 39618 open source projects for "java-ml"
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Don’t let unpaid invoices limit your business’s growth. EBizCharge plugs directly into the tools your business already uses to speed up payment collection.
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Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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Apache Avro
Apache Avro is a data serialization system
Apache Avro™ is a data serialization system. Simple integration with dynamic languages. Code generation is not required to read or write data files nor to use or implement RPC protocols. Code generation is an optional optimization, is only worth implementing for statically typed languages. Avro relies on schemas. When Avro data is read, the schema used when writing it is always present. This permits each datum to be written with no per-value overheads, making serialization both fast and... -
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Bisq
A decentralized bitcoin exchange network
Buy and sell bitcoin for fiat (or other cryptocurrencies) privately and securely using Bisq's peer-to-peer network and open-source desktop software. No registration is required. Get started in minutes. No need to wait for approval from a central authority. Trading takes place on a global P2P network of users running Bisq on their own machines. Bisq never holds your funds. Deposits held in 2-of-2 multi-sig wallets encourage safe, successful trades. Your data is stored locally on disk, and is... -
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ElasticJob
Distributed scheduled job framework
ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud. ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services. ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and... -
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Coca
Coca is a toolbox which is design for legacy system refactoring
Coca is a toolbox that is design for legacy system refactoring and analysis, including call graph, concept analysis, api tree, and design patterns suggestions. Requirements: graphviz for dot file to image (such as svg, png). The easiest way to get coca is to use one of the pre-built release binaries which are available for OSX, Linux, and Windows on the release page. -
With Twilio Voice, you can build unique phone call experiences with one API, to create, receive, control and monitor calls with just a few lines of code. Create an engaging voice experience that you can quickly scale and modify with a wide array of customization options and resources.
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SCIPIO ERP
eCommerce framework for multinational omnichannel installations
High-performance DNA for your custom ONLINE SHOP. A flexible composable commerce framework for international and complex multichannel webshops! Scipio ERP is a perfect fit for large-scale, multinational, multichannel operations. Our modern eCommerce store is optimized for a quick time-to-market. You can run multiple at the same time. Highly configurable products and prices, custom promotions and region-based offerings – the store can handle it all. Our web store is mobile-friendly and full... -
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Android Contacts, Reborn
Android Contacts API Library written in Kotlin
This library provides a complete set of APIs to do everything you need with Contacts in Android. You no longer have to deal with the Contacts Provider, database operations, and cursors. Whether you just need to get all or some Contacts for a small part of your app (written in Kotlin or Java), or you are looking to create your own full-fledged Contacts app with the same capabilities as the AOSP Android Contacts app and Google Contacts app, this library is for you. -
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Timbre
Pure Clojure/Script logging library
Java logging can be a Kafkaesque mess of complexity that buys you little. Getting even the simplest logging working can be comically hard, and it often gets worse at scale as your needs become more sophisticated. Timbre offers an all Clojure/Script alternative that's fast, deeply flexible, easy to configure with pure Clojure data, and that just works out the box. No XML. Easily filter logging calls by any combination of: level, namespace, and appended. Zero overhead compile-time level/ns... -
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Intellij rainbow brackets
Rainbow Brackets for IntelliJ based IDEs/Android Studio/HUAWEI DevEco
Compatible with IntelliJ IDEA, PhpStorm, WebStorm, PyCharm, RubyMine, AppCode, CLion, Gogland, DataGrip, Rider, MPS, Android Studio, HUAWEI DevEco Studio, DataSpell, Code With Me. Supports Java, Scala, Clojure, Kotlin, Python, Haskell, Agda, Rust, JavaScript, TypeScript, Erlang, Go, Groovy, Ruby, Elixir, ObjectiveC, PHP, HTML, XML, SQL, Apex language, C#, Dart, Pug/Jade, Bash, Vue.js, C# Razor Pages, GLSL(the OpenGL Shading Language), Go Template, C++, C, etc. Eliminate context switching... -
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Jaeger
Monitor and troubleshoot transactions in complex distributed systems
.... It is used for monitoring and troubleshooting microservices-based distributed systems. OpenTracing compatible data model and instrumentation libraries include Go, Java, Node, Python, C++ and C#. Jaeger uses consistent upfront sampling with individual per service/endpoint probabilities and it has multiple storage backends: Cassandra, Elasticsearch, memory. -
PRTG Network Monitor is an all-inclusive monitoring software solution developed by Paessler. Equipped with an easy-to-use, intuitive interface with a cutting-edge monitoring engine, PRTG Network Monitor optimizes connections and workloads as well as reduces operational costs by avoiding outages while saving time and controlling service level agreements (SLAs). The solution is packed with specialized monitoring features that include flexible alerting, cluster failover solution, distributed monitoring, in-depth reporting, maps and dashboards, and more.
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XGBoost
Scalable and Flexible Gradient Boosting
... can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
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V Programming Language
Simple, fast, safe, compiled language for developing software
... in the first place by using value types, and string buffers, promoting a simple abstraction-free code style. Most objects (~90-100%) are freed by V's auto-free engine: the compiler inserts necessary free calls automatically during compilation. A remaining small percentage of objects is freed via GC. The developer doesn't need to change anything in their code. "It just works", like in Python, Go, or Java, except there's no heavy GC tracing everything or expensive RC for each object. -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid... -
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Application Inspector
A source code analyzer built for surfacing features of interest
Microsoft Application Inspector is a software source code characterization tool that helps identify coding features of first or third party software components based on well-known library/API calls and is helpful in security and non-security use cases. It uses hundreds of rules and regex patterns to surface interesting characteristics of source code to aid in determining what the software is or what it does from what file operations it uses, encryption, shell operations, cloud API's,... -
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BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads... -
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TFX
TFX is an end-to-end platform for deploying production ML pipelines
TensorFlow Extended (TFX) is a Google-production-scale machine learning platform based on TensorFlow. It provides a configuration framework to express ML pipelines consisting of TFX components. TFX pipelines can be orchestrated using Apache Airflow and Kubeflow Pipelines. Both the components themselves and the integrations with orchestration systems can be extended. TFX components interact with an ML Metadata backend that keeps a record of component runs, input and output artifacts, and runtime... -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine... -
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AutoMLPipeline.jl
Package that makes it trivial to create and evaluate machine learning
AutoMLPipeline (AMLP) is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica... -
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AutoGluon
AutoGluon: AutoML for Image, Text, and Tabular Data
AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning, model... -
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Kubeflow Training Operator
Distributed ML Training and Fine-Tuning on Kubernetes
Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and scalable distributed training of machine learning (ML) models created with various ML frameworks such as PyTorch, TensorFlow, XGBoost, MPI, Paddle, and others. -
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Flower
Flower: A Friendly Federated Learning Framework
A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state... -
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LangKit
An open-source toolkit for monitoring Language Learning Models (LLMs)
LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible with the open-source data logging library whylogs. Productionizing language models, including LLMs, comes with a range of risks due to the infinite amount of input combinations, which can elicit an infinite amount of outputs. The unstructured nature of text poses a challenge in the ML observability... -
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Data Annotator for Machine Learning
Data annotator for machine learning
Data annotator for machine learning allows you to centrally create, manage and administer annotation projects for machine learning. Data Annotator for Machine Learning (DAML) is an application that helps machine learning teams facilitate the creation and management of annotations. Active learning with uncertain sampling to query unlabeled data. Project tracking with real-time data aggregation and review process. User management panel with role-based access control. -
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KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary... -
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ZenML
Build portable, production-ready MLOps pipelines
A simple yet powerful open-source framework that scales your MLOps stack with your needs. Set up ZenML in a matter of minutes, and start with all the tools you already use. Gradually scale up your MLOps stack by switching out components whenever your training or deployment requirements change. Keep up with the latest changes in the MLOps world and easily integrate any new developments. Define simple and clear ML workflows without wasting time on boilerplate tooling or infrastructure code. Write... -
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ODD Platform
First open-source data discovery and observability platform
Unlock the power of big data with OpenDataDiscovery Platform. Experience seamless end-to-end insights, powered by unprecedented observability and trust - from ingestion to production - while building your ideal tech stack! Democratize data and accelerate insights. Find data that fits your use case and discover hints left by your peers to leverage existing knowledge. Explore tags, ownership details, links to other sources and other information to shorten and simplify data discovery phase....