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This is a Object Detection Answering model from TensorFlow Hub

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

This is a Image Classification model from TensorFlow Hub

It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies the second sentence entails the first sentence, and the no-entailment implies it does not. The Text Embedding model which is pre-trained on English and German Wikipedia returns an embedding of the input pair of sentences. The model available for deployment is created by attaching a binary classification layer to the output of the Text Embedding model, and the

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of question-context strings. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

This is a Extractive Question Answering model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/ ). It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of question-context strings.

Our AI-based Passport Scanning Recognition System would reduce the need for 60 office workers employed manual verification and tracking. Additionally, the has a real time automated data entry tool to streamline and maintain the database of over 100,000 aviation personnel.

The Nitro Enclaves Developer AMI contains the necessary tools and components to build enclave applications. It also contains samples, such as hello-enclave, vsock_sample and kmstool, to demonstrate how to use and develop your own enclave applications.

The Prebuilt configuration reduces implementation time and costs compared to custom ERP solutions developed from the ground up. Pre-build ERPNext with WooCommerce allows businesses to quickly get up and running on a fully functional ERP system that can scale as they grow. Role-based access controls secure sensitive data. Support for multiple companies, currencies, taxes, and locations provides flexibility.

Apache OFBiz is a powerful top-level Apache software project. OFBiz is an Enterprise Resource Planning (ERP) System written in Java and houses a large set of libraries, entities, services, and features to run all aspects of your business. A prebuilt OFBiz AMI contains the OFBiz framework and a set of preconfigured modules and features ready for deployment. The preconfigured modules cover areas like accounting, inventory management, e-commerce, CRM.

Apache OFBiz is A powerful top-level Apache software project. OFBiz is an Enterprise Resource Planning (ERP) System written in Java and houses a large set of libraries, entities, services, and features to run all aspects of your business. A prebuilt OFBIZ ECR image contains the OFBIZ framework and a set of preconfigured modules and features ready for deployment. The preconfigured modules cover areas like accounting, inventory management, e-commerce, and CRM.

ERPNext is a modern tool that covers accounting and many other business functions on an integrated platform. Our Pre-build ERPNext is a ready-to-use enterprise resource planning (ERP) system. It includes core modules, features, dashboards, and reports required to manage critical business functions including multiple workflows to get businesses up and running quickly for accounting, sales, purchasing, inventory, manufacturing, HR, payroll, and CRM.

Automated CICD Jenkins: SonarQube and OWASP Code Testing is a powerful solution for streamlined DevOps automation. With this integrated approach, developers can use our pre-built pipelines meeting dynamic scenarios. Jenkins stack is tightly coupled with SonarQube Scanner ensuring efficient code analysis and application security testing with OWASP ZAP. Experience improved code quality and reduced vulnerabilities with this integrated approach, extending the pipeline favour to automate application

Deploy Infrastructure as Code - (IaC) based automated Containerized Application on AWS ECS Fargate Stack with enhanced security, CloudWatch monitoring, EFS integration, and a seamless Jenkins CI/CD pipeline for continuous delivery.

Datadog is a comprehensive monitoring and security platform designed for cloud-scale applications, offering real-time observability of servers, databases, tools, and services. It enables organizations to monitor their entire infrastructure, detect and resolve issues swiftly, and optimize performance across various environments. Key Features and Functionality: - Infrastructure Monitoring: Provides real-time visibility into cloud and on-premises environments, ensuring optimal performance and ava

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