machine-learning

Near-optimal vector quantization from Google's ICLR 2026 paper — 95% recall, 5x compression, zero preprocessing, pure Python FAISS replacement

HTK Toolkit with Linux 64 bit and Docker support

Why is LLM inference slow — and how do you make it fast? A hands-on, first-principles course: roofline → KV cache → quantization → parallelism → vLLM/SGLang, with GPU labs on open models.

indoBERT Base-Uncased fine-tuned on Translated Squad v2.0

PostgreSQL-native semantic search engine with multi-modal capabilities. Add AI-powered search to your existing database without separate vector databases, vendor fees, or complex setup. Features text + image search using CLIP embeddings, native SQL joins, and 10-minute Docker deployment.

Docker build of postgresql changing the dimension limit for the cube extension, raising it to 350

A curated list of tools, frameworks, and resources for running AI locally — inference, RAG, orchestration, monitoring, and more.

Implementation of TSDS: Data Selection for Task-Specific Model Finetuning. An optimal-transport framework for selecting domain-specific and task-specific training data to improve LLM finetuning and instruction tuning.

A dataset of high level chess games for training machine learning models.

End-To-End Machine Learning Project for Automatic Grades for Student Essays

Toolchain for creating custom datasets and training Stable Diffusion (1.x, 2.x, XL) models and LoRAs

Rust server that summarizes text with pre-trained models

A starter kit for evaluating benchmarks on the 🤗 Hub

"Solace AI: Your Empathetic Digital Confidant": Solace AI is an empathetic mental health companion that understands your emotions and personality to provide personalized support through natural conversations. It creates a judgment-free space where you can express yourself freely and receive compassionate guidance tailored just for you.

A comprehensive, production-focused guide to acing AI/ML system design interviews at top tech companies.

An interactive web application for comparing PDF documents using cosine similarity scans and a chatbot interface to explore and interact with PDF content.

i have build speech recognition app using mozilla deepspeech

Local inference server for Apple Silicon — hot-swaps MLX models (LLM, vision, embeddings, TTS, STT) via OpenAI API

A Content Based And A Hybrid Recommender System using content based filtering and Collaborative filtering

Object-storage-native KV cache for LLM inference & RL. Cross-restart, cross-conversation, cross-engine via shared S3 bucket.