4.8 out of 5 stars
(30 Ratings)
JDisc Discovery is a comprehensive network inventory and IT asset management solution designed to help organizations gain clear, up-to-date visibility into their IT environment. It automatically scans and maps devices across the network, including servers, workstations, virtual machines, and network hardware, to create a detailed inventory of all connected assets. This includes critical information such as hardware configurations, software installations, patch levels, and relationshipots between devices.
One of the standout features of JDisc Discovery is its agentless discovery process, meaning it does not require the installation of any software on individual devices, reducing deployment time and minimizing network impact. It supports a wide range of protocols (e.g., SNMP, SSH, WMI) to gather data, making it compatible with diverse IT environments, whether they are Windows, Linux, or Unix-based.
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4.8 out of 5 stars
(64 Ratings)
SurveyJS is an embeddable, self-hosted, white-label form builder for teams building custom forms, surveys, questionnaires, and other data collection tools inside web applications. It runs entirely on the client and is fully compatible with all modern JavaScript frameworks, including React, Angular, and Vue. SurveyJS integrates with any backend, giving you full control over data, security, user access, deployment, and business logic. Instead of hardcoding forms, you can empower non-technical users to generate and edit JSON schema-based form configurations through a drag-and-drop form builder.
Create dynamic forms with custom conditional logic, validation, multilingual support, PDF export, and analytics. Ideal for SaaS, enterprise software, HR, healthcare, fintech, and other regulated industries, SurveyJS helps teams reduce engineering effort, standardize data collection, maintain full control over data, and deliver unlimited forms that match their brand and feel native to users.
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TensorBoard
TensorBoard is TensorFlow's comprehensive visualization toolkit designed to facilitate machine learning experimentation. It enables users to track and visualize metrics such as loss and accuracy, visualize the model graph (operations and layers), view histograms of weights, biases, or other tensors as they change over time, project embeddings to a lower-dimensional space, and display images, text, and audio data. Additionally, TensorBoard offers profiling capabilities to optimize TensorFlow programs. These features collectively provide a suite of tools to understand, debug, and optimize TensorFlow programs, enhancing the machine learning workflow. In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics, visualizing the model graph, and projecting embeddings to a lower dimensional space.
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