Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.
-
Updated
Apr 6, 2026 - Jupyter Notebook
Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.
A Python package to assess and improve fairness of machine learning models.
Official implementation of Meta Prompting for AI Systems (https://arxiv.org/abs/2311.11482)
Practical system design, tools, and hands-on resources for building Gen-AI agents & agentic AI systems.
IdenProf dataset is a collection of images of identifiable professionals. It is been collected to enable the development of AI systems that can serve by identifying people and the nature of their job by simply looking at an image, just like humans can do.
An innovative AI system developed to extract actionable insights by converting natural language into SQL queries via Google's Gemini model and dynamically visualizing the data with Plotly Express, streamlining decision-making across all levels of expertise.
A curated list of AI safety resources: alignment, interpretability, governance, verification, and responsible deployment of frontier AI systems.
Saturn accelerates the training of large-scale deep learning models with a novel joint optimization approach.
EPI (Evidence Packaged Infrastructure) packages AI execution as evidence.
Resources for recent AI systems (deployment concerns, cost and accessibility). -- closed
Source repo for the blog post Stop Stuffing Your System Prompt: Build Scalable Agent Skills in LangGraph
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.
🧾 Open, hands-on AI education program — from Machine Learning to Generative Intelligence. Weekly lessons in Jupyter Notebooks, ready for Google Colab.🧾
Organize your AI agent teams with the Viable System Model. The missing organizational layer for multi-agent systems.
Prototype for Block, a new LLM-multi instance scheduling Framework
Welcome to the repository for **Exercise 3 of the AI Systems Course** at the **University of Tehran**. This project focuses on designing and implementing a lightweight, efficient **processing element (PE)** for performing operations of neurons in a **multi-layer perceptron (MLP)** using Verilog.
This project uses AI-powered vehicle detection to enable customizable and efficient parking space management.
Algorithmic inspection for trustworthy ML models
A local control plane for Model Context Protocol (MCP) servers — unify stdio and HTTP MCP tools behind a single, secure local endpoint.
Main entry point to the TrackieWay Project, with the entire ecosystem
Add a description, image, and links to the ai-systems topic page so that developers can more easily learn about it.
To associate your repository with the ai-systems topic, visit your repo's landing page and select "manage topics."