Search Results for "function point"
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Showing 7 open source projects for "function point"
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SIEM | API Security | Log Management SoftwareBuilt on the Graylog Platform, Graylog Security is the industry’s best-of-breed threat detection, investigation, and response (TDIR) solution. It simplifies analysts’ day-to-day cybersecurity activities with an unmatched workflow and user experience while simultaneously providing short- and long-term budget flexibility in the form of low total cost of ownership (TCO) that CISOs covet. With Graylog Security, security analysts can:
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Shoplogix Smart Factory PlatformReal-time Visibility into Your Shop Floor's Performance. The Shoplogix smart factory platform enables manufacturers to increase overall equipment effectiveness, reduce operational costs, sustain growth and improve profitability by allowing them to visualize, integrate and act on production and machine performance in real-time. Manufacturers that trust us to drive efficiency in their factories. Real-time visual data and analytics provide valuable insights to make better informed decisions. Uncover hidden shop floor potential and drive rapid time to value. Develop a continuously improving culture through training, education and data-driven decisions. Compete in the i4.0 world by making the Shoplogix Smart Factory Platform the cornerstone of your digital transformation. Connect to any equipment or device to automate data collection and exchange it with other manufacturing technologies. Automatically monitor, report and analyze machine states to track real-time production.
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
Code-Mode is a plug-and-play library that lets AI agents call tools by executing TypeScript (or via a Python wrapper) instead of making many individual function calls. Its core philosophy is that language models are very good at writing code, so rather than exposing hundreds of separate tool endpoints, you give the model a single “code execution” tool that has access to your full toolkit through code. This approach can dramatically reduce the number of tool-call iterations needed in complex... -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and... -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ... -
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Point-E
Point cloud diffusion for 3D model synthesis
...While it does not match the fine detail of some slower methods, the tradeoff in speed makes it practical for prototyping and interactive 3D generation. The repository includes inference scripts, utilities for converting point clouds to meshes (e.g. via signed distance function regression), sample notebooks, and weight checkpoints. It also provides documentation on limitations, usage instructions, and example outputs. -
SalesTarget.ai | AI-Powered Lead Generation, Email Outreach, and CRMSalesTarget is ideal for B2B sales teams, startup founders, and marketing professionals looking to streamline lead generation and outreach. It also benefits growing SaaS companies and agencies aiming to scale their outbound efforts efficiently.
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
...A tensor can be thought of as an n-dimensional matrix. In the CNN above, tensors will be 3-dimensional with the exception of the output layer. A neuron can be thought of as a function that takes in multiple inputs and yields a single output. The outputs of neurons are represented above as the red → blue activation maps. -
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TensorNets
High level network definitions with pre-trained weights in TensorFlow
High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and... -
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physicsmata
API for all possible cellular automata that work same at all angles
...Its parameters are sums of screen brightness (n color dimensions are optional) at concentric circles around each point, efficiently costing only the perimeter of those circles (instead of the area) because of the tree of squares. You can create any function, or to get started try the visual function editor where each click changes if a column is sine/sigmoid/half/double/exp/etc or which of the 0, 1, or 2 columns to the left are its params. Every click changes the patterns of waves seen on the left, which run that function you visually built at each point.
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