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Source channel @githubtrending · Post #14926 · Jul 8

#jupyter_notebook#artificial_intelligence#book#large_language_models#llm#llms#oreilly#oreilly_books You can learn how to use Large Language Models (LLMs) effectively through the book *Hands-On Large Language Models* by Jay Alammar and Maarten Grootendorst. This book uses nearly 300 custom illustrations to explain key concepts and practical tools for working with LLMs, including tokenization, transformers, prompt engineering, fine-tuning, and advanced text generation. It also provides runnable code examples in Google Colab, making it easy to practice and apply what you learn. This resource helps you understand and build your own LLM applications confidently, saving you time and effort in mastering complex AI technology. It’s highly recommended for anyone wanting hands-on experience with LLMs. https://github.com/HandsOnLLM/Hands-On-Large-Language-Models

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@githubtrending · Post #15456 · 01/31/2026, 04:30 PM

#typescript#investigation#osint#python#recon Flowsint is a free, open-source tool for OSINT investigations that visualizes data like domains, IPs, emails, phones, crypto wallets, and websites as interactive graphs to spot hidden links fast. Install easily with Docker and Make via git clone and "make prod," then run locally at localhost:5173 for full privacy—all data stays on your machine. With 30+ auto-enrichers (e.g., subdomain scans, WHOIS, breach checks), it chains tasks to automate deep recon, saving hours on manual work and revealing patterns for cybersecurity, journalism, or fraud probes ethically. https://github.com/reconurge/flowsint

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@githubtrending · Post #15103 · 08/30/2025, 11:30 AM

#python#blueteam#discovery#emails#information_gathering#osint#python#recon#reconnaissance#redteam#subdomain_enumeration theHarvester is a free, easy-to-use tool that helps you gather public information about a domain, such as emails, subdomains, IPs, and URLs, from many online sources like search engines and databases. It is useful during security testing to understand a company’s external exposure and find potential vulnerabilities. You can run it with Python and it supports features like DNS brute forcing and taking screenshots of found subdomains. Using theHarvester helps you quickly collect valuable data for cybersecurity assessments, making your research more efficient and thorough. https://github.com/laramies/theHarvester