👨🏻‍💻 This Python library helps you extract usable data for language models from complex files like tables, images, charts, or multi-page documents.

📝 The idea of Agentic Document Extraction is that unlike common methods like OCR that only read text, it can also understand the structure and relationships between different parts of the document. For example, it understands which title belongs to which table or image.


✅ Works with PDFs, images, and website links.

☑️ Can chunk and process very large documents (up to 1000 pages) by itself.

✔️ Outputs both JSON and Markdown formats.

☑️ Even specifies the exact location of each section on the page.

✔️ Supports parallel and batch processing.

pip install agentic-doc

┌ 🥵 Agentic Document Extraction
├ 🌎 Website
└ 🐱 GitHub Repos

🌐 #DataScience #DataScience
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https://t.me/CodeProgrammer

📺 12 comprehensive playlists to master
⬅️ machine learning, deep learning, and GenAI!


👨🏻‍💻 Each playlist is designed to be simple and understandable for beginners, and then gradually dive deeper into the topics.


😉 Machine Learning Basics (39 videos)

😉 Python for ML (9 videos)

😉 Optimization for ML (5 videos)

😉 Machine Learning with Practical Exercises (37 videos)

😉 Building Decision Trees from Scratch (13 videos)

😉 Building Neural Networks from Scratch (35 videos)

😉 Graph Neural Networks (6 videos)

😉 Computer Vision from Scratch (19 videos)

😉 Building LLM from Scratch (43 videos)

😉 Reasoning in LLMs from Scratch (22 videos)

😉 Building DeepSeek from Scratch (29 videos)

😉 Machine Learning in Production Environment (6 videos)



🌐 #Data_Science #DataScience
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https://t.me/CodeProgrammer ❤️

💠 The Best Tool for Extracting Data from PDF Files!

👩🏻‍💻 Usually, PDF files like financial reports, scientific articles, or data analyses are full of tables, formulas, and complex texts.

⬅️ Most tools only extract texts and destroy the data structure, causing important information to be lost.

✅ But the tool Docling uses artificial intelligence to preserve all those structures (text, tables, formulas) exactly as they are in the file. Then it converts that data into a structured format. Meaning AI models can work on them.

⭕ The interesting point is that with just three lines of Python code, you can convert any PDF into searchable data!

┌ 🥵 Docling
├ 🔎 Article
├ 📄 Documentation
└ 🐱 GitHub-Repos

🌐 #Data_Science #DataScience
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⚙️ This tool is turning the world of Web Scraping upside down!

👨🏻‍💻 A new tool called Crawl4AI has been introduced that makes Web Scraping and data extraction from websites much easier, faster, and smarter! Especially designed for use in AI models like ChatGPT and similar tools.

1⃣ Its special features:

🔹 Completely free and open-source. That means you can use it however you want without any cost.

🔹 Works much faster than paid tools.

🔹 Its outputs are AI-friendly, such as JSON, HTML, or Markdown.

🔹 Can extract data from multiple websites simultaneously.

🔹 Collects images, videos, and audio from pages as well.

🔹 Extracts all internal and external links for you.
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🔢 More advanced features:

🔹 Takes screenshots of pages and collects metadata (like title, description, tags).

🔹 You can write custom code or special settings like auth and headers.

🔹 You can even change its browser User-Agent to behave like a human.

🔹 Before starting extraction, it can run your custom JavaScript code.

┌ ♦️ Crawl4AI
└ 🐱 GitHub Repos

🌐 #DataScience #DataScience

https://t.me/CodeProgrammer