ai-interview-codex offers a practical AI interview prep guide featuring iterative system design for Agentic AI and RAG, with benchmarks and production insights for ML, LLM, and system design roles.
AI-ML-Cheatsheets offers a modular, offline-ready collection of concise AI/ML reference sheets from foundational math to transformers and large language models.
Autodistill automates the pipeline from large foundation models to edge-ready vision models using pluggable plugins and a natural language ontology for zero-shot labeling.
Bytez offers a unified API for over 220,000 AI models with serverless GPU orchestration, abstracting model diversity into a single inference platform accessible via one key.
DeepSpeed is a Python library that optimizes large-scale deep learning training with multi-hardware support and JIT CUDA extensions. Explore its architecture, strengths, and quick installation.
Fast3R from Meta FAIR processes 1000+ unordered images simultaneously for 3D reconstruction using a ViT-Large backbone and multi-view attention, eliminating iterative matching.
gnnpapers is a curated, community-recognized bibliography of 800+ must-read graph neural network papers. It organizes GNN research evolution and applications without any code.
Mini-SGLang is a modular Python reimplementation of the SGLang LLM inference engine with production features like Radix Cache, chunked prefill, overlap scheduling, and tensor parallelism.
Kimi-Audio combines continuous acoustic and discrete semantic tokens within a 7B LLM for unified audio-text understanding and generation. It achieves state-of-the-art ASR with low-latency audio synthesis.
Lynx generates personalized videos from a single image using a frozen Diffusion Transformer with ID and Ref adapters. This modular design balances fidelity and efficiency.
Mathematics-for-ML is a curated repository aggregating key resources on the mathematical foundations of machine learning. It collects books, papers, and lectures to build strong math intuition for ML practitioners.
ML-From-Scratch offers bare-bones Python implementations of key machine learning algorithms using only NumPy, focusing on transparency over efficiency. Explore how it demystifies ML fundamentals.
MLJobSearch2025 offers a curated tier list of AI employers by compensation and a rich set of ML interview questions, helping candidates targeting $300K+ roles prepare effectively.
A practical guide to bishwaghimire’s AI learning roadmaps repository, offering modular, career-focused paths for AI and ML self-learners, with setup essentials and a flexible curriculum.
The LLM Engineer Handbook catalogs the full lifecycle of large language model engineering, from pretraining to prompt management, guiding engineers beyond demos to production-ready LLM apps.
Nougat is Meta’s neural OCR system for academic PDFs, extracting LaTeX math and tables into structured Markdown using a Vision Transformer encoder-decoder. It offers CLI, API, and training tools.
OverlapNet uses Siamese networks on 2D range images from 3D LiDAR to detect loop closures by predicting overlap and relative yaw angle simultaneously. Practical demos included.
SafestClaw uses classical ML pipelines and local AI models to deliver 90% of OpenClaw’s features at zero cost, avoiding prompt injection and cloud dependencies.
vLLM Compressor applies advanced quantization and compression techniques to large language models, enabling optimized inference without requiring full model definitions.
YuE is an open-source Python foundation model for generating complete songs from lyrics using a two-stage architecture and audio in-context learning. It supports style cloning and LoRA finetuning under Apache 2.0.
