Scrape Google AI Mode responses without blocks on a large scale.

Structured data gathering from any website using AI-powered scraper, crawler, and browser automation. Scraping and crawling with natural language prompts. Equip your LLM agents with fresh data. AI Studio python SDK for intelligent web data gathering.

Fast ML inference & training for ONNX models in Rust

Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

AI Scraper is a powerful scraping tool and scrape agent built to automate data extraction with unmatched precision. Ideal for scalable AI scraping tasks across diverse web sources, this tool simplifies complex scraping operations into efficient, intelligent workflows.

oneAPI Data Analytics Library (oneDAL)

Execute complex automation scripts via remote cloud sessions , featuring integrated residential proxies , automated CAPTCHA solving , and native JavaScript rendering for the toughest dynamic websites.

Official Oxylabs AI-Studio Openclaw plugin

oneAPI Collective Communications Library (oneCCL)

The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.

GPU Cluster Monitoring (GCM): Large-Scale AI Research Cluster Monitoring

Turn plain English queries into structured web data, featuring automated markdown extraction and full JavaScript rendering for dynamic websites.

Detailed Guide on How to Contribute to Gensyn RL-Swarm

Easily download all of your favorite Naughty images from multiple sites.

This is a dataset intended to train a LLM model for a completely CVE focused input and output.

Vailabel Studio - a local-first desktop studio that labels your data with an offline AI copilot. Private by default. Windows, macOS, Linux.

Master AI prompting for business innovation. O'Reilly Live Learning course by Tim Warner covering ChatGPT, Claude, Copilot, and enterprise prompt engineering with MCP implementation.

A highly memory-efficient fine-tuning toolkit for SDXL and ANIMA, combining modern VRAM-saving techniques with custom optimizers to enable full-quality model training on GPUs with as little as 12 GB of VRAM.

Client library to interact with various APIs used within Philips in a simple and uniform way

A step-by-step walkthrough of the inner workings of a simple neural network. The goal is to demystify the calculations behind neural networks by breaking them down into understandable components, including forward propagation, backpropagation, gradient calculations, and parameter updates.