Search Results for "technologies"
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Showing 19 open source projects for "technologies"
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Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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DeepCamera
Open-Source AI Camera. Empower any camera/CCTV
DeepCamera empowers your traditional surveillance cameras and CCTV/NVR with machine learning technologies. It provides open-source facial recognition-based intrusion detection, fall detection, and parking lot monitoring with the inference engine on your local device. SharpAI-hub is the cloud hosting for AI applications that helps you deploy AI applications with your CCTV camera on your edge device in minutes. SharpAI yolov7_reid is an open-source Python application that leverages AI technologies to detect intruders with traditional surveillance cameras. ... -
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Compute Library
The Compute Library is a set of computer vision and machine learning
The Compute Library is a set of computer vision and machine learning functions optimized for both Arm CPUs and GPUs using SIMD technologies. The library provides superior performance to other open-source alternatives and immediate support for new Arm® technologies e.g. SVE2. -
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zvt
Modular quant framework
For practical trading, a complex algorithm is fragile, a complex algorithm building on a complex facility is more fragile, complex algorithm building on a complex facility by a complex team is more and more fragile. zvt wants to provide a simple facility for building a straightforward algorithm. Technologies come and technologies go, but market insight is forever. Your world is built by core concepts inside you, so it’s you. zvt world is built by core concepts inside the market, so it’s zvt. The core concept of the system is visual, and the name of the interface corresponds to it one-to-one, so it is also uniform and extensible. You can write and run the strategy in your favorite ide, and then view its related targets, factor, signal and performance on the UI. ... -
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PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework
PaddlePaddle is an open source deep learning industrial platform with advanced technologies and a rich set of features that make innovation and application of deep learning easier. It is the only independent R&D deep learning platform in China, and has been widely adopted in various sectors including manufacturing, agriculture and enterprise service. PaddlePaddle covers core deep learning frameworks, basic model libraries, end-to-end development kits and more, with support for both dynamic and static graphs. -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
...With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers, embedded, or automotive product platforms. TensorRT is built on CUDA®, NVIDIA’s parallel programming model, and enables you to optimize inference leveraging libraries, development tools, and technologies in CUDA-X™ for artificial intelligence, autonomous machines, high-performance computing, and graphics. With new NVIDIA Ampere Architecture GPUs, TensorRT also leverages sparse tensor cores providing an additional performance boost. -
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Qlib
Qlib is an AI-oriented quantitative investment platform
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. With Qlib, users can easily try their ideas to create better Quant investment strategies. At the module level, Qlib is a platform that consists of above components. ... -
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Spice.ai OSS
A self-hostable CDN for databases
...Spice connects, fuses, and delivers data to applications, machine-learning models, and AI backends, functioning as an application-specific, tier-optimized Database CDN. The Spice runtime, written in Rust, is built-with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB. Spice makes it easy and fast to query data from one or more sources using SQL. You can co-locate a managed dataset with your application or machine learning model, and accelerate it with Arrow in-memory, SQLite/DuckDB, or with attached PostgreSQL for fast, high-concurrency, low-latency queries. ... -
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AutoMLOps
Build MLOps Pipelines in Minutes
...The service generates a containerized MLOps codebase, provides infrastructure-as-code to provision and maintain the underlying MLOps infra, and provides deployment functionalities to trigger and run MLOps pipelines. AutoMLOps gives flexibility over the tools and technologies used in the MLOps pipelines, allowing users to choose from a wide range of options for artifact repositories, build tools, provisioning tools, orchestration frameworks, and source code repositories. AutoMLOps can be configured to either use existing infra, or provision new infra, including source code repositories for versioning the generated MLOps codebase, build configs and triggers, artifact repositories for storing docker containers, storage buckets, etc. -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
...It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting. -
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The SpeechBrain Toolkit
A PyTorch-based Speech Toolkit
SpeechBrain is an open-source and all-in-one conversational AI toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains. SpeechBrain supports state-of-the-art methods for end-to-end speech recognition, including models based on CTC, CTC+attention, transducers, transformers, and neural language models relying on recurrent neural networks and transformers. Speaker recognition is already deployed in a... -
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Jina
Build cross-modal and multimodal applications on the cloud
Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP, GraphQL protocols with TLS. Intuitive design pattern for high-performance microservices. Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. ... -
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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T81 558
Applications of Deep Neural Networks
Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. -
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MTBook
Machine Translation: Foundations and Models
This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. ... -
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ML.NET Samples
Samples for ML.NET, an open source and cross-platform machine learning
...In this GitHub repo, we provide samples that will help you get started with ML.NET and how to infuse ML into existing and new .NET apps. We're working on simplifying ML.NET usage with additional technologies that automate the creation of the model for you so you don't need to write the code by yourself to train a model, you simply need to provide your datasets. The "best" model and the code for running it will be generated for you. The ML.NET CLI (command-line interface) is a tool you can run on any command prompt (Windows, Mac or Linux) for generating good quality ML.NET models based on training datasets you provide. ... -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and compare the results. ... -
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Pragmatic AI
[Book-2019] Pragmatic AI: An Introduction to Cloud-based ML
Pragmatic AI is the first truly practical guide to solving real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Writing for business professionals, decision-makers, and students who aren’t professional data scientists, Noah Gift demystifies all the tools and technologies you need to get results. He illuminates powerful off-the-shelf cloud-based solutions from Google, Amazon, and Microsoft, as well as accessible techniques using Python and R. Throughout, you’ll find simple, clear, and effective working solutions that show how to apply machine learning, AI and cloud computing together in virtually any organization, creating solutions that deliver results, and offer virtually unlimited scalability. -
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JCLTP
A Java Class Library for Text Processing
JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types of information is much easier and intuitive. The researcher can use the class library by adding it to his project or direct through specific commands created for these cases. ... -
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English-Khmer S. Machine Translation
English-Khmer Automatic Statistic Machine Translation (SMT)
Automatic Machine Translation from English to Khmer project is the first effort in Natural Language Processing field for translating English to Khmer (Cambodian) language. This project uses Domy CE, an open source SMT toolkit, for training parallel corpus and web technologies such as Python, Apache2, HTML, XML, and XSLT for developing web-based application. This project is developed by Ms. Kim Sokphyrum (DU) and Ms. Suos Samak (Jamia), under Supervision of Mr. Javier Sola, a Program Manager at Open Institute (OI), Cambodia, Dr. Vasudha Bhatnagar, an Assistant professor and a Head of Computer Science at University of Delhi (DU), New Delhi, India. and Dr. ...
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