Showing 11 open source projects for "self learning"

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  • 1
    AgentEvolver

    AgentEvolver

    Towards Efficient Self-Evolving Agent System

    AgentEvolver is an open-source research framework for building self-evolving AI agents powered by large language models. The system focuses on improving the efficiency and scalability of training autonomous agents by allowing them to generate tasks, explore environments, and refine strategies without heavy reliance on manually curated datasets. Its architecture combines reinforcement learning with LLM-driven reasoning mechanisms to guide exploration and learning.
    Downloads: 3 This Week
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  • 2
    SwanLab

    SwanLab

    An open-source, modern-design AI training tracking and visualization

    ...SwanLab supports both cloud and self-hosted deployments, allowing organizations to run the system privately or integrate it into shared development environments. The platform integrates with a wide range of machine learning frameworks including PyTorch, Transformers, Keras, and other widely used training ecosystems.
    Downloads: 5 This Week
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  • 3
    AudioMuse-AI

    AudioMuse-AI

    AudioMuse-AI is an Open Source Dockerized environment

    ...By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal music libraries and generate curated playlists for different moods or listening contexts. AudioMuse-AI integrates with several popular self-hosted music servers including Jellyfin, Navidrome, and Emby, allowing users to extend existing media servers with advanced AI-powered recommendation capabilities. The system uses machine learning and audio analysis tools such as Librosa and ONNX models to extract features directly from audio tracks.
    Downloads: 41 This Week
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  • 4
    OpenOutreach

    OpenOutreach

    Linkedin Automation Tool

    ...According to the repository, it combines large language model classification with a Bayesian machine learning layer based on profile embeddings, which helps it shift from broad exploration to more confident qualification as it gathers more decisions. It is designed to automate personalized outreach as well, including connection requests and follow-up messaging, while keeping deployment under the user’s control through a local or self-hosted setup.
    Downloads: 0 This Week
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  • 5
    Learn AI Engineering

    Learn AI Engineering

    Learn AI and LLMs from scratch using free resources

    ...The curation recognizes modern AI realities, including data pipelines, evaluation, prompt engineering, retrieval-augmented generation, and cost/performance trade-offs. It’s equally useful for refreshers—dipping into a specific module before a project—as it is for a full, self-directed curriculum. By centralizing the best references in one place, the repo reduces the overhead of finding, filtering, and sequencing resources, letting you focus on learning and building.
    Downloads: 0 This Week
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  • 6
    AI Engineering Transition Path

    AI Engineering Transition Path

    Research papers and blogs to transition to AI Engineering

    AI Engineering Resources is an open educational repository that compiles research papers, tutorials, and learning materials for software engineers transitioning into artificial intelligence engineering roles. The project organizes resources that cover fundamental topics required to understand modern AI systems, including transformers, vector embeddings, tokenization, infrastructure design, and mixture-of-experts architectures. Instead of presenting isolated tutorials, the repository provides...
    Downloads: 0 This Week
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  • 7
    Agentic Context Engine

    Agentic Context Engine

    Make your agents learn from experience

    Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and...
    Downloads: 15 This Week
    Last Update:
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  • 8
    hCaptcha Challenger

    hCaptcha Challenger

    Gracefully face hCaptcha challenge with multimodal llms

    hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks...
    Downloads: 16 This Week
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  • 9
    Prompt Engineering Techniques

    Prompt Engineering Techniques

    Collection of tutorials for Prompt Engineering techniques

    ...It is intended for a wide audience, from beginners learning how to structure their first prompts to advanced practitioners optimizing stability, controllability, and reliability in production systems.
    Downloads: 0 This Week
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  • 10
    Agents 2.0

    Agents 2.0

    An Open-source Framework for Data-centric Language Agents

    Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During...
    Downloads: 0 This Week
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  • 11
    Transformer Explainer

    Transformer Explainer

    Learn How LLM Transformer Models Work with Interactive Visualization

    Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward...
    Downloads: 0 This Week
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