⚡ HKUDS/DeepTutor is making waves. Here's the full picture.

🔗 https://github.com/HKUDS/DeepTutor
📝 DeepTutor: Lifelong Personalized Tutoring.https://deeptutor.info/.
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The DeepTutor project is a lifelong personalized tutoring system. Its key features include a knowledge graph, question bank, and chat interface for conversing with Partners - AI personas with their own skills and memory. To get started, users can install DeepTutor and access its web interface for configuration and usage.
The project has a strong focus on community, with a Discord channel and Feishu group for discussion and collaboration.
Technical highlights of the project include its use of Python 3.11+, Next.js 16, and various AI and machine learning technologies.
The project is licensed under Apache 2.0 and has a GitHub release available.
DeepTutor is suitable for educators, researchers, and developers interested in AI-powered education and tutoring systems.
One-liner takeaway: DeepTutor is revolutionizing education with its AI-powered personalized tutoring system, making learning more effective and engaging for all.

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🧠 Channel: https://t.iss.one/GithubRe

📌 Spotted on GitHub Trending: HenryNdubuaku/maths-cs-ai-compendium — let's break it down.

🔗 https://github.com/HenryNdubuaku/maths-cs-ai-compendium
📝 Become a cracked AI/ML Research Engineer
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The Maths, CS & AI Compendium is an unconventional, open textbook covering maths, computing, and artificial intelligence from the ground up. It's designed for curious practitioners seeking a deep understanding of the subject matter, not just exam or interview survival.

Key features include intuition-first explanations, real-world context, and no hand-waving of complex concepts. The compendium also comes with an MCP server that lets AI assistants use it as a knowledge base, along with tools for educational purposes and example implementations.

The compendium is organized into 18 chapters, covering topics such as vectors, matrices, calculus, statistics, probability, machine learning, computational linguistics, computer vision, and more. It's written in a way that's easy to follow, with a focus on pattern recognition and quality knowledge consumption.

The target audience is anyone looking to gain a solid foundation in maths, CS, and AI, from students to working professionals. To get the most out of the compendium, readers can use the Phase 1 and Phase 2 study techniques outlined in the README.

Here's a sample

Python code

to give you an idea of the type of content included.

In short, the Maths, CS & AI Compendium is a valuable resource for anyone looking to deepen their understanding of these subjects. The one-liner takeaway: with persistence and the right resources, anyone can become a proficient maths, CS, and AI practitioner.

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🧠 Channel: https://t.iss.one/GithubRe

📌 Spotted on GitHub Trending: Shubhamsaboo/awesome-llm-apps — let's break it down.

🔗 https://github.com/Shubhamsaboo/awesome-llm-apps
📝 100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
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Awsome LLM Apps is a GitHub repository that offers 100+ open-source AI agents, agent skills, and RAG apps that are hand-built, tested end-to-end, and available under the Apache-2.0 license. The repository provides a wide range of AI applications, including agent skills, starter AI agents, advanced AI agents, and always-on agents. These applications can be used for various purposes, such as project management, insurance claims, fraud investigation, and more. The repository also includes multi-agent teams that can collaborate to accomplish complex tasks. To get started, users can clone the repository and run the agents using pip install and streamlit run. The repository is suitable for developers, researchers, and anyone interested in exploring the potential of AI applications. Take your AI journey to the next level with Awesome LLM Apps - clone, customize, and deploy your own AI agents in minutes!

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🧠 Channel: https://t.iss.one/GithubRe

🎯 coreyhaines31/marketingskills landed on trending. Worth a proper look.

🔗 https://github.com/coreyhaines31/marketingskills
📝 Marketing skills for Claude Code and AI agents. CRO, copywriting, SEO, analytics, and growth engineering.
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The coreyhaines31/marketingskills GitHub repository is a collection of AI agent skills focused on marketing tasks, built for technical marketers and founders. These skills enable AI coding agents to assist with various marketing activities, such as conversion optimization, copywriting, SEO, analytics, and growth engineering.

Key features include a range of skills that reference each other, building on shared context, with the product-marketing skill serving as the foundation. The repository provides a comprehensive list of available skills, including ab-testing, ad-creative, seo-audit, and many more.

To get started, users can install the skills using the CLI install option. The repository also offers a companion guide, Coding for Marketers, for those new to the terminal and coding agents.

The target audience includes technical marketers, founders, and anyone looking to leverage AI-powered marketing skills. With its extensive range of skills and user-friendly installation process, this repository is an invaluable resource for those seeking to enhance their marketing capabilities.

One-liner takeaway: Unlock the full potential of AI-powered marketing with the coreyhaines31/marketingskills repository and take your marketing efforts to the next level!

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🧠 Channel: https://t.iss.one/GithubRe

⚡ YimMenu/YimMenuV2 is making waves. Here's the full picture.

🔗 https://github.com/YimMenu/YimMenuV2
📝 Experimental menu for GTA 5: Enhanced
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The YimMenuV2 repository is a C++20 mod menu base that serves as a learning opportunity for its creator. The project's structure is divided into three main directories: core/ for essential features, game/ for game-specific implementations, and util/ for general utility functions. This base is designed to provide a foundation for modding, with a focus on templating and experimentation. It's geared towards developers looking to explore C++20 and mod menu development. The takeaway: Learning by doing is the best way to template your way to mod menu mastery!

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🧠 Channel: https://t.iss.one/GithubRe

🌟 hasaneyldrm/exercises-dataset caught my eye on GitHub Trending today.

🔗 https://github.com/hasaneyldrm/exercises-dataset
📝 1,324-exercise fitness dataset — animation GIFs, 180×180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
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The exercises-dataset repository, created by hasaneyldrm, is a comprehensive collection of 1,324 fitness exercises, each with an animation GIF, 180×180 thumbnail image, category, body-part, equipment, target and muscle-group data, and step-by-step instructions in 9 languages. The dataset is designed for building fitness or workout planning applications, machine learning projects, health and wellness research, and educational demonstrations.

Key features of the dataset include:
- 1,324 exercises with detailed metadata
- Animation GIFs and thumbnails for each exercise
- Step-by-step instructions in 9 languages
- Interactive browser for easy exploration of exercises

The dataset is MIT licensed, with additional media terms. It powers the LogPress app, an AI-assisted workout tracker, and can be easily integrated into other applications.

The dataset is suitable for developers, researchers, and fitness enthusiasts looking to build or enhance their fitness-related projects.

One-liner takeaway: With the exercises-dataset, you can supercharge your fitness app with a vast, high-quality collection of exercises and metadata.

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🧠 Channel: https://t.iss.one/GithubRe

🔥 apache/ossie is trending — and it deserves your attention.

🔗 https://github.com/apache/ossie
📝 Apache Ossie, industry wide specification effort to standardize how we exchange semantic metadata across analytics, AI and BI platforms, providing a vendor neutral, single source of truth for semantic data
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Apache Ossie is a collaborative effort to standardize semantic model exchange and utilization across data analytics, AI, and BI tools. The goal is to establish a vendor-agnostic semantic model specification for unparalleled interoperability and efficiency. This project provides a single JSON- and YAML-based specification that tools can read and write, addressing semantic fragmentation.

Key features include a core-spec for the Ossie specification, converters for translating between Ossie and other formats, and examples of semantic models. The project also offers tooling for validation against the Ossie schema.

Audience: data analysts, AI professionals, and BI practitioners seeking to streamline their workflows. To get involved, contribute code, participate in discussions, or join the Slack community.

Here's a glimpse of the code:

{
  "spec": "ossie-spec"
}

One-liner takeaway: Apache Ossie is the key to unlocking seamless data exchange and utilization across your entire tool stack!

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🧠 Channel: https://t.iss.one/GithubRe