LangExtract

A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.

GitHub: https://github.com/google/langextract

https://t.iss.one/DataScience4 🖕

This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://t.iss.one/addlist/8_rRW2scgfRhOTc0

✅ https://t.iss.one/Codeprogrammer

✅ open-source alternative to Perplexity.

✅ Real-time web search with Firecrawl API
✅ Advanced answers with GPT-4o-mini
✅ Every sentence with reference and source
✅ Automatic stock display with TradingView


┌ 🔍 Fireplexity
├ 🥵 Website
└ 🐱 GitHub-Repos

https://t.iss.one/DataScienceN 🌟

🧱 AI now generates worlds in the style of Minecraft — presenting the GameFactory model

Researchers trained the model on 70 hours of Minecraft gameplay and achieved impressive results: 
GameFactory can create procedural game worlds — from volcanoes to cherry blossom forests, just like in the iconic simulator.

🔥 Want your own endless world? Just set the parameters.

🟠 Examples and code — at the link: https://yujiwen.github.io/gamefactory/

🟠Github: https://github.com/KwaiVGI/GameFactory

https://t.iss.one/DataScienceN 🌟

python-docx: Create and Modify Word Documents #python

python-docx is a Python library for reading, creating, and updating Microsoft Word 2007+ (.docx) files.

Installation

pip install python-docx

Example

from docx import Document

document = Document()
document.add_paragraph("It was a dark and stormy night.")
<docx.text.paragraph.Paragraph object at 0x10f19e760>
document.save("dark-and-stormy.docx")

document = Document("dark-and-stormy.docx")
document.paragraphs[0].text
'It was a dark and stormy night.'

https://t.iss.one/DataScienceN 🚗

Data scientists, this is for you — I dug up LeetCode for DS

DataLemur — a powerful platform that collects real interview problems from Tesla, Facebook, Twitter, Microsoft, and other top companies

Inside: practical tasks on SQL, statistics, Python, and ML. You can filter by difficulty level and company

Top-notch for those preparing for interviews for Data Scientist / Data Analyst roles. Get it here 🍯

👉 https://t.iss.one/DataScienceN 👍