Machine Learning
identification through experience.
See Also: Artificial Intelligence, Identification
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Open Source Machine Learning server
PredictionIO
The Apache Software Foundation
Apache PredictionIO is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. It lets you: quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically;unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; etc.
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Open Source Computer Vision & Machine Learning Software Library
OpenCV
Open Source Computer Vision Library
The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc.
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Azure Machine Learning
Empower data scientists and developers with a wide range of productive experiences to build, train, and deploy machine learning models and foster team collaboration. Accelerate time to market with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible machine learning.
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Video Encoding and Machine Learning
Fraunhofer Institute for Telecommunications
With the proliferation of video in our everyday lives, the efficient coding, transport, processing and analysis of video signals is becoming more and more important. The Department of Video Coding and Machine Learning is concerned with image and video coding, transport of multimedia data, design of embedded systems for multimedia processing as well as analysis and machine understanding of images and videos.
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Alteryx Machine Learning Platform
https://www.alteryx.com/products/alteryx-machine-learning#:~:text=Scale%20data%20science%20across%20your%20business%20with%20automated%20machine%20learning%20(AutoML)%20and%20feature%20engineering%2C%20empowering%20business%20domain%20experts%20and%20data%20scientists%20alike%20to%20accelerate%20insights.
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Azure Stream Analytics
Discover Azure Stream Analytics, the easy-to-use, real-time analytics service that is designed for mission-critical workloads. Build an end-to-end serverless streaming pipeline with just a few clicks. Go from zero to production in minutes using SQL—easily extensible with custom code and built-in machine learning capabilities for more advanced scenarios. Run your most demanding workloads with the confidence of a financially backed SLA.
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Total Moisture Control
SKALA
Advanced machine learning algorithm to generate actionable dashboards, optimize the drying process, and boost your revenue.
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Nano Family
The Nano Family is a set of boards with a tiny footprint, packed with features. It ranges from the inexpensive, basic Nano Every, to the more feature-packed Nano 33 BLE Sense / Nano RP2040 Connect that has Bluetooth® / Wi-Fi radio modules. These boards also have a set of embedded sensors, such as temperature/humidity, pressure, gesture, microphone and more. They can also be programmed with MicroPython and supports Machine Learning.
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Digital Twin
Engineering simulation software has traditionally been used for new product design, but with the advent of advanced embedded sensors, engineers can now use this data to create digital twins. Digital twins can be used in real-time systems analysis to schedule predictive maintenance and implement performance optimizations. With the Hybrid Analytics capability of Ansys, engineers can reach an unparalleled level of accuracy using predictive analytics by combining machine learning (ML)-based analytics with a physics-based approach.
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GPGPU Board
NVP2009
As part of our NVIDIA Pascal™ based chip-down series of GPU XMC products the NVP2009 is ideal for GPGPU applications such as C5ISR, situational awareness, signal intelligence (SIGINT), as well as machine learning and autonomy.
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Mobile Network Testing Products
The Rohde & Schwarz mobile network testing (MNT) portfolio consists of standalone products and integrated solutions covering all use cases and test scenarios along the lifecycle of a mobile network. The modular, scalable and future-proof portfolio comprises specially engineered hardware for high-quality data collection, including a versatile range of test scenario-based hardware options, as well as a sophisticated software suite to gain machine learning assisted deep insights.
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Microsoft Graph Data Connect
Microsoft Graph is the Microsoft 365 data that describes the patterns of productivity, identity, and security in an organization. Microsoft Graph Data Connect offers developers a highly secure, efficient way to copy Microsoft Graph datasets, at scale, into Azure Data Factory. It's an ideal way to train AI and machine learning models that uncover rich organizational insights and deliver new value to your productivity solutions.
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TySOM Embedded Prototyping Boards
TySOM™ is a family of embedded system prototyping boards. Depending on the board, one of three FPGAs will be at its heart: a Xilinx Zynq® UltraScale+™, a Xilinx Xilinx Zynq-7000 or a Microchip PolarFire SoC. The boards are compatible, through industry standard interfaces (FMC or BPX), with Aldec’s wide range daughter cards, making Aldec’s TySOM embedded prototyping boards ideal for the rapid development of applications that include automotive (and ADAS, in particular), artificial intelligence (AI), machine learning (ML), embedded vision, embedded-HPC (including edge-processing), IoT, IIoT and industrial automation.
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PCIe 4.0 Ethernet Controller
BCM57504
Based on Broadcom’s scalable 10/25/50/100/200G Ethernet controller architecture, the NetXtreme®-E Series BCM57504 100G PCIe 4.0 Ethernet controller is designed to build highly-scalable, feature-rich networking solutions in servers for enterprise and cloud-scale networking and storage applications, including high-performance computing, telco, machine learning, storage disaggregation, and data analytics.
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Embedded Computing Modules
Curtiss-Wright Defense Solutions
Our selection of rugged, embedded computing modules has been trusted and proven in defense, commercial, and industrial applications worldwide. Choose from solutions with hardened security, high-performance processing for machine learning and artificial intelligence (AI), and SWaP-optimized, miniature form factors to meet your program requirements.
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6U VPX GPGPU Processing Cards
Curtiss-Wright Defense Solutions
For systems requiring compute-intensive capability or using deep learning frameworks for AI applications, these highly engineered modules provide a field-proven hardware foundation. These processing powerhouses leverage the latest GPGPU advancements from NVIDIA for machine learning and artificial intelligence applications.
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PCIe OCP 3.0 Ethernet Adapter
N1100G
Based on Broadcom’s scalable 10/25/50/100/200G Ethernet controller architecture, the NetXtreme®-E Series N1100G 1x100G OCP 3.0 adapter is designed to build highly scalable, feature-rich networking solutions in servers for enterprise and cloud-scale networking and storage applications, including high-performance computing, telco, machine learning, storage disaggregation and data analytics.
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GPGPU Cards
Curtiss-Wright Defense Solutions
For applications requiring massive parallel compute capability, such as deep learning frameworks for AI applications, our highly engineered GPGPU co-processing engines provide a field-proven hardware foundation. Curtiss-Wright GPGPU co-processing engines leverage the latest NVIDIA Tensor Cores (for machine learning) technology and are a critical component of the high-performance embedded computing (HPEC) ecosystem that delivers data center capability at the tactical edge.
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PCIe 3.0 Ethernet Controller
BCM57412
Based on Broadcom’s scalable 10/25/50/100/200G Ethernet controller architecture, the NetXtreme®-E Series BCM57412 25G PCIe 3.0 Ethernet controller is designed to build highly-scalable, feature-rich networking solutions in servers for enterprise and cloud-scale networking and storage applications, including high-performance computing, telco, machine learning, storage disaggregation, and data analytics.
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Data Center
InnoLight Technology Corporation
New applications such as digital reality, artificial intelligence, machine learning are driving the network traffic to an unprecedented level. Cloud operators need continuing innovation in optical solutions to support bandwidth demand. InnoLight's comprehensive family of optical transceivers, including 10G, 25G, 40G, 100G, 200G, 400G and 800G will enable cloud operators to rapidly upgrade its network.
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Signal And Image Processing Research
TPAC solutions are ideal for research in signal processing applied to ultrasound. You need to be able to access to any parameter, implement a particular algorithm, and access to any data during the acquisition or postprocessing phase. TPAC provides you all of these. It can be applied to studies in signal processing, image processing, beamforming, machine learning, etc… Thanks to TPAC’s open platforms, you will be able to freely set the ultrasonic sequences, record the raw data from your experiment, and test your own algorithms or even method. In order to adapt to a wide variety of habits, TPAC proposes multiple APIs (Application Programming Interface) compatible with Matlab, C++, Python, C#, Labview and working under Windows or Linux operating systems. Through a socket, it is even possible to use any OS of your choice.
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PathWave Waveform Analytics Software
Debug voltage and current spikes, IO glitches, and time shifts in pre-silicon using powerful machine learning.
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I-Pi SMARC Development Kit based on NXP® i.MX 8M Plus Quad Arm® Cortex-A53 Processor
I-Pi SMARC IMX8M Plus
The I-Pi SMARC IMX8M Plus is a SMARC-based smart solution development kit powered by NXP i.MX8M Plus (Quad-core Arm Cortex-A53) processor with a Neural Processing Unit (NPU) at up to 2.3 TOPS.This is the first SMARC R2.1 development kit focused on machine learning, vision, advanced multimedia, and industrial IoT with high reliability. As such, it supports dual image processors and two camera inputs for an effective Vision System, as well as applications beyond, including smart homes, building cities, and industry 4.0.
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Lattice SensAI Studio
Graphical interface based tool to help users built accelerated machine learning applications quickly. Select from a range of models pretrained to cover popular use cases, bring in your own data for additional training, validation the quality of training using TensorBoard, compile for Lattice’s FPGAs*Model Zoo with variety of models based on multiple architecture*Easy to use labeling, training, and compilation GUI*Docker container provided for installation on your own machine or server*Free license
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Cognitive Computing
Watson
IBM Watson is a technology platform that uses natural language processing and machine learning to reveal insights from large amounts of unstructured data
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Internet Of Things
IoT
In a world of smart, connected everything, Altair empowers you to harness the power of the Internet of Things (IoT) to accelerate innovation and unlock business value. Leveraging our dynamic toolset you can deploy edge compute clusters, train and execute machine learning models, implement complex application business logic, perform data transforms, visualize real-time data, and much more. We give you the building blocks for your digital transformation to get moving fast, scale quickly, and continue to improve over time.
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Text Analysis
Text analytics is the process of transforming unstructured text documents into usable, structured data. Text analysis works by breaking apart sentences and phrases into their components, and then evaluating each part’s role and meaning using complex software rules and machine learning algorithms. Data analysts and other professionals use text mining tools to derive useful information and context-rich insights from large volumes of raw text, such as social media comments, online reviews, and news articles. In this way, text analytics software forms the backbone of business intelligence programs, including voice of customer/customer experience management, social listening and media monitoring, and voice of employee/workforce analytics.
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Dual-Port 10G PCIe Ethernet NIC
P210P
Based on Broadcom’s scalable 10/25/50/100/200G Ethernet controller architecture, the NetXtreme®-E Series P210P 2x10G PCIe NIC is designed to build highly-scalable, feature-rich networking solutions in servers for enterprise and cloud-scale networking and storage applications, including high-performance computing, telco, machine learning, storage disaggregation, and data analytics.
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Camera Automation System
Overcam
Overcam® automates key camera positions around the field of play, helping live sports productions gain extra camera coverage at lower operational costs. Based on robotized cameras and machine learning algorithms, the innovative system delivers high-quality shots with an optimal framing of the action. Designed to work in real-time and offering a dedicated feature set for soccer and basketball productions, Overcam® will seamlessly integrate into your existing multicamera live productions, providing your teams with more options for storytelling.
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Artificial Intelligence And Machine Learning Testing
AI and ML testing framework can efficiently recognize pitfalls and with constant updates to the algorithms, it is feasible to discover even the negligible error. Essentially, Artificial Intelligence (AI) and Machine Learning (ML) tech are well-trained to process data, identify schemes and patterns, form and evaluate tests without human support. This is made possible with deep learning and artificial neural networks when a machine self-educates based on the given data sets or data extracted from an external source such as the web.
