Search Results for "//sourceforge.net/projects/shanaencoder/" - Page 3
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Showing 128 open source projects for "//sourceforge.net/projects/shanaencoder/"
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Cycloid: Hybrid Cloud DevOps collaboration platformEnable your developers to do their best work and increase time-to-market speed with a leading DevOps and Hybrid Cloud platform.
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Self-hosted password managerOn-premise solution with double encryption and certified development processes for maximum protection of corporate data. Zero‑knowledge architecture ensures your passwords never leave your infrastructure.
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machine_learning_examples
A collection of machine learning examples and tutorials
...The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. Many of the examples are accompanied by tutorials and educational materials that explain how the algorithms work and how they can be applied in real-world projects. The code is organized into small independent experiments so that learners can explore specific algorithms or techniques without needing to understand the entire codebase. -
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OpenPlanter
Language-model investigation agent with a terminal UI
...It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. The system is structured to support experimentation and customization, making it suitable for both research and DIY agriculture projects. With its modular Python codebase, users can adapt the platform for different plant types, hardware setups, or automation strategies. Overall, OpenPlanter aims to simplify the creation of programmable, data-driven plant care systems. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training... -
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AI Engineering from Scratch
Learn it. Build it. Ship it for others
AI Engineering from Scratch is a comprehensive open-source curriculum designed to teach artificial intelligence by building every component from first principles rather than relying on prebuilt frameworks. The project is structured into more than 20 phases and hundreds of lessons, covering topics that range from foundational mathematics to advanced systems such as large language models, retrieval pipelines, and multi-agent architectures. Each lesson emphasizes hands-on implementation,... -
Rev Your Digital Product Delivery EnginePlanview links your technology vision directly to teams' daily work, providing complete visibility and control over your digital product delivery ecosystem.
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. Each example is designed to illustrate a single... -
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Hephaestus
Semi-Structured Agentic Framework. Workflows build themselves
Hephaestus is an open-source semi-structured agentic framework designed to orchestrate multiple AI agents working together on complex tasks. Instead of relying entirely on predefined workflows, the framework allows agents to dynamically create tasks as they explore a problem space. Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression,... -
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LangBot
Production-grade platform for building agentic IM bots
...It supports numerous messaging services including Discord, Slack, Telegram, WeChat, and other enterprise communication systems, making it a flexible solution for both personal projects and organizational deployments. LangBot combines LLM capabilities with agent logic, knowledge base orchestration, and plugin infrastructure so that bots can perform complex tasks rather than simple conversational responses. The platform includes a web-based management interface that simplifies configuration, access control, and integration with external AI services. -
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TaskingAI
Open platform for building, deploying, and managing LLM agents
...It includes a modular architecture that supports components such as assistants, tools, retrieval systems, and conversation management, all accessible through a consistent interface. TaskingAI also provides a built-in user interface for managing projects, testing workflows, and configuring AI agents without needing to rely entirely on code. It supports advanced techniques like retrieval-augmented generation and plugin-based extensions, allowing developers to enhance agent capabilities. -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and applications step by step. ... -
Pylon is an All-in-one B2B Support Platform for modern B2B businesses.We bring together everything a post-sales teams team needs including a ticketing system, B2B omnichannel integrations (Slack Connect, Microsoft Teams), modern chat widget, knowledge base, AI support bot, account management, customer marketing, and more.
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis.... -
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AI Engineer Headquarters
A collection of scientific methods, processes, algorithms
AI-Engineer-Headquarters is a comprehensive educational repository designed to help developers become advanced AI engineers through a structured learning path and practical system-building exercises. The project serves as a curated collection of resources, methodologies, and tools covering topics across the entire artificial intelligence development lifecycle. Rather than focusing only on theoretical knowledge, the repository emphasizes applied learning and encourages engineers to build real... -
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Made With ML
Learn how to develop, deploy and iterate on production-grade ML
Made-With-ML is an open-source educational repository and course designed to teach developers how to build production-grade machine learning systems using modern MLOps practices. The project focuses on bridging the gap between experimental machine learning notebooks and real-world software systems that can be deployed, monitored, and maintained at scale. It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets,... -
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AICGSecEval
A.S.E (AICGSecEval) is a repository-level AI-generated code security
AICGSecEval is an open-source benchmark framework designed to evaluate the security of code generated by artificial intelligence systems. The project was developed to address concerns that AI-assisted programming tools may produce insecure code containing vulnerabilities such as injection flaws or unsafe logic. The framework constructs evaluation tasks based on real-world software repositories and known vulnerability cases derived from CVE records. By simulating realistic development... -
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E2M
E2M converts various file types (doc, docx, epub, html, htm, url
E2M is a SourceForge mirror of the e2m open-source project, which focuses on providing tools or services designed to convert or process content between different formats or systems. Projects with similar naming conventions typically emphasize automation workflows where input data from one environment is transformed into another representation or output structure. The mirrored repository allows users to access the project’s codebase independently from its original hosting platform while preserving the development history and release artifacts. ... -
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HuixiangDou
Overcoming Group Chat Scenarios with LLM-based Technical Assistance
...The assistant uses retrieval and ranking methods along with language model reasoning to produce accurate answers for technical topics such as computer vision and machine learning projects. It can be integrated into messaging platforms such as WeChat or other team collaboration tools to assist developer communities. -
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ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools... -
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Trail of Bits Skills Marketplace
Trail of Bits Claude Code skills for security research, vulnerability
...This project leverages the agent skills architecture to let AI assistants take on detailed, repeatable security procedures that are typically manual, such as parsing Burp Suite projects or conducting variant analysis across codebases. -
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Live Agent Studio
Open source AI Agents hosted on the oTTomator Live Agent Studio
...Each agent in the collection is designed for a specific use case — such as content summarization, task automation, travel planning, or RAG workflows — and is provided with the code or configuration needed to explore and extend it on your own, making the repository both a learning resource and a practical starting point for real projects. The repository is community focused, with sample agents like tweet generators, smart selectors, research assistants, and multi-tool workflows that show how agents can integrate with tools like n8n or custom Python code. Because it’s tied to the broader Live Agent Studio ecosystem, users can experiment with deploying and using these agents in a hosted environment. -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
...With a local-first design, your data stays private and portable, while optional cloud sync enables cross-device access. It combines simplicity with powerful indexing and search, giving you a flexible way to build long-term memory for projects, research, and workflows. -
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Pal
A personal context-agent that learns how you work
Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can... -
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AgentScope
Build and run agents you can see, understand and trust
AgentScope is a production-ready agent framework designed to help developers build, deploy, and scale intelligent agentic applications. It provides essential abstractions that evolve with advancing LLM capabilities, emphasizing reasoning, tool use, and flexible orchestration rather than rigid prompt constraints. With built-in support for ReAct agents, memory, planning, human-in-the-loop control, and real-time voice interaction, developers can create powerful agents in minutes. AgentScope... -
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DGL
Python package built to ease deep learning on graph
...Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. ... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
...When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. In addition to code analysis, the tool can produce daily development summaries and notifications that help teams track progress and review activity across projects. -
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OSS-Fuzz Gen
LLM powered fuzzing via OSS-Fuzz
...The system integrates with modern LLM-assisted workflows to draft harness code and then iterates based on build errors or low coverage signals. Importantly, it aligns with OSS-Fuzz conventions, generating corpus seeds, build rules, and sanitizer settings so projects can plug in quickly. Reports highlight what functions were targeted, how coverage evolved, and where manual hints could unlock more paths. The goal is pragmatic: shrink the gap between “we should fuzz this” and “we have robust fuzzing running in CI,” especially for understaffed maintainers. -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection....
