This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
TensorZero creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.
An AI-powered data science team of agents to help you perform common data science tasks 10X faster.
AI Driven Machine Automation Platform 🚀🚀
Datasets for Predictive Maintenance
A list of AI memory projects
Explore a curated collection of exceptional open-source libraries for generative AI meticulously reviewed or slated for review by The AI Engineer. Contribute your own projects to be considered for evaluation and inclusion in this dynamic repository dedicated to advancing the AI engineering discipline.
Essential reads for every AI engineer interested in building AI apps.
Claude Plus is an advanced AI-powered development assistant that combines the capabilities of Anthropic's Claude AI with a suite of development tools.
My solutions to Quizzes and Programming Assignments of the specialization.
🧾 | Use these AI prompts to refine your searches, improve accuracy, and get detailed, context-driven responses that precisely match your queries.
👋 AI Multi-Agent Engineer Portfolio I'm Idael, an AI Prompt Engineer and Network Automation specialist at Kyndryl, focused on transforming complex challenges into innovative solutions through multi-agent systems.
This repository contains course content related to the IBM AI Engineering Specialization, aimed at providing comprehensive insights and skills in the field of Artificial Intelligence.
Backend server for AGI OS - Awesome Gamer Insight Orchestrating System
A modular, multi-agent AI research and report generation platform. Enter any topic, and PolyAgent Research Intelligence orchestrates multiple AI agents to retrieve literature, analyze data, and generate a polished report. Built for researchers and AI/ML engineers, leveraging LangChain, FastAPI, PostgreSQL, advanced LLMs, and a Next.js front-end.
A machine learning pipeline taking you from raw data to fully trained machine learning model - from data to model (d2m).
A list of resources for AI engineers
AI Engineering: Annotated NBs to dive into Self-Attention, In-Context Learning, RAG, Knowledge-Graphs, Fine-Tuning, Model Optimization, and many more.
Simple Multi-Resource Rate Limiting That Saves Unused Tokens. Rate limit API requests across different resources and workers without wasting your quota. Reserve tokens upfront, get refunds for what you don't use, and avoid over-limiting.
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