Data Science Jupyter Notebooks
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Explore the world of Data Science through Jupyter Notebooksβ€”insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
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πŸš€ AutoPilot β€” a free automation suite that replaces a dozen services at once

If you love tools that save time, money, and nerves β€” this is 100% for you.

This is an open-source panel on Python + Streamlit, packed with a whole arsenal of useful automations.

You open it β€” and it’s like gaining a superpower: doing everything faster.

What it can do:
πŸ–Ό Background Remover β€” removes photo backgrounds in a second.
🧾 QR Generator β€” creates QR codes for anything.
πŸ’» Fake Data Generator β€” generates realistic test data.
🎧 Audiobook Converter β€” turns PDFs into audiobooks.
πŸ“₯ YouTube Downloader β€” downloads video and audio.
πŸ’¬ Bulk Email Sender β€” mass email sending.
πŸ“Έ Image Downloader β€” searches and downloads images by keywords.
πŸ“ Article Summarizer β€” creates well-written concise summaries.
πŸ“Š Resource Monitor β€” monitors your system resources.
πŸ” Code Analyzer β€” checks code with Pylint and Flake8.
🧹 Clipboard Manager β€” stores clipboard history.
πŸ”— Link Checker β€” checks which links are alive.
πŸ“· Image Editor β€” a mini-Photoshop: crop, blur, resize, watermark, formatting, and lots of effects.
πŸ—ž News Reader β€” reads out current news.

And that’s just part of the list.

Why do you need this?
🟒 a ready set of utilities for developers, marketers, designers, or SMM;
🟒 huge time savings;
🟒 local, free, and without limits;
🟒 can be integrated into your projects, bots, or workflow.

⚑️ How to run (quickly)

git clone https://github.com/Ai-Quill/automated.git
cd automated
pip install -r requirements.txt
streamlit run app.py


πŸ–₯Open in your browser: http://localhost:8501

And enjoy the panel where all tools are just one click away.

β™ŽοΈ GitHub/Instructions

#python #soft #github

https://t.me/DataScienceN 🌟
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Deepnote has released a new open notebook format that solves the old problems of Jupyter.

Instead of noisy JSON, now YAML with proper git diff. Support for Python and SQL in one file, shared project settings, new blocks for charts and SQL, proper teamwork and collaborative editing. Conversion from .ipynb in one step. Everything is open-source. πŸ’ƒ
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Data Science Jupyter Notebooks
πŸ’Έ PacketSDK--A New Way To Make Revenue From Your Apps Regardless of whether your app is on desktop, mobile, TV, or Unity platforms, no matter which app monetization tools you’re using, PacketSDK can bring you additional revenue! ● Working Principle: Convert…
I want to share a tool that I genuinely believe can make a real difference for anyone building apps: PacketSDK. Many developers have strong active-user bases but still struggle to increase revenue. That’s exactly why this solution stands outβ€”it adds extra income without disrupting users or interfering with your existing monetization methods.

Why I strongly recommend it:

* It turns your active users into immediate profit without showing ads.
* Integration is fast and straightforwardβ€”around 30 minutes.
* It works on all platforms: mobile, desktop, TV, Unity, and more.

As a channel owner, I recommend trying this service; you have nothing to lose.

I used it and found its earnings amazing.
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It was a challenge - a marathon 300$ to 30.000$ on trading, together with Lisa!

What is the essence of earning?: "Analyze and open a deal on the exchange, knowing where the currency rate will go. Lisa trades every day and posts signals on her channel for free."

πŸ”ΉStart: $150
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πŸ”ΉPeriod: 1.5 months.

Join and get started, there will be no second chanceπŸ‘‡

https://t.me/+L9_l-dxOJxI2ZGUy
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Demo of Yann LeCun's convolutional neural network from 1989. Modern CNNs that we still use today are based on it.

It's amazing how far we've come since then 🌟

πŸ‘‰ https://t.me/DataScienceN
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If you love automating everything, this is for you

AutoPilot is an open-source panel built with #Python + #Streamlit, packed with a whole arsenal of useful automations.

Open it, and you have tools at your fingertips like background removal for photos, QR code generation, YouTube downloading, fake data creation, audiobooks, email sending, code analysis, image editing, and even a news reader.

One window instead of a dozen services. πŸ™‚
https://github.com/Ai-Quill/automated


πŸ‘‰ https://t.me/DataScienceN
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πŸŒ† RMBG

πŸ› οΈ RMBG is a new AI background removal model that significantly outperforms its counterparts.

πŸ”° It effectively separates the foreground and background for various types of images, providing high accuracy and commercial applicability.

πŸ”— Links:
https://github.com/Bria-AI/RMBG-2.0/

🏷️ Tags: #ai #imageeditor

https://t.me/DataScienceN ⚑️
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πŸ‘¨β€πŸ’» Wren AI

πŸ›  Wren AI is an AI agent that allows users to request data in natural language and receive accurate SQL queries, charts, and analytical reports within seconds.

πŸ”° It provides capabilities for data interaction, insight generation, and includes a semantic layer that ensures the accuracy of conclusions.

πŸ”° API integration enables the creation of custom agents and chatbots.

🌟 The platform supports multiple databases and is compatible with various LLM models.

πŸ”— Links:
https://github.com/Canner/WrenAI

πŸ–€Tags: #ai #agents #sql #llm
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A new Python library for agent-based data-processing and ETL using AI has been released.

Introducing DocETL.

What is important to know:

1. What is DocETL?

It is a tool for creating and running data pipelines, especially well-suited for complex document processing.

It includes:

- interactive UI playground
- Python package for running pipelines in production

2. DocWrangler

DocWrangler helps gradually build the pipeline:

- trying different prompts and viewing results in real-time
- building the pipeline step by step
- exporting the final configuration for production

3. Python package DocETL

It is used for running pipelines in production. In the example, a pipeline is created that analyzes medical transcripts, identifies drug names, normalizes similar names, and generates summaries of side effects and areas of application.

More information: https://github.com/ucbepic/docetl

πŸ‘‰ https://t.me/DataScienceN
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πŸ”₯ Trending Repository: Memori

πŸ“ Description: Open-Source Memory Engine for LLMs, AI Agents & Multi-Agent Systems

πŸ”— Repository URL: https://github.com/MemoriLabs/Memori

🌐 Website: https://memorilabs.ai

πŸ“– Readme: https://github.com/MemoriLabs/Memori#readme

πŸ“Š Statistics:
🌟 Stars: 8.8K stars
πŸ‘€ Watchers: 46
🍴 Forks: 629 forks

πŸ’» Programming Languages: Python - PLpgSQL

🏷️ Related Topics:
#python #agent #awesome #state_management #ai #memory #memory_management #hacktoberfest #long_short_term_memory #rag #llm #memori_ai #hacktoberfest2025 #chatgpt #aiagent


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🧠 By: https://t.me/DataScienceM
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Sometimes you get lost in a large Markdown file? That won't happen anymore.

treemd is an interactive navigator for Markdown with a header tree that can be collapsed.

Read Markdown like code.

Two windows, vim-style navigation, live search, and synchronized scrolling.

πŸ¦€ Written in Rust, built on top of ratatui

GitHub: https://github.com/Epistates/treemd

πŸ‘‰  https://t.me/DataScienceN
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πŸŽβ—οΈTODAY FREEβ—οΈπŸŽ

Entry to our VIP channel is completely free today. Tomorrow it will cost $500! πŸ”₯

JOIN πŸ‘‡

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πŸ”₯ Trending Repository: fizzy

πŸ“ Description: Kanban as it should be. Not as it has been.

πŸ”— Repository URL: https://github.com/basecamp/fizzy

🌐 Website: https://fizzy.do

πŸ“– Readme: https://github.com/basecamp/fizzy#readme

πŸ“Š Statistics:
🌟 Stars: 2.4K stars
πŸ‘€ Watchers: 27
🍴 Forks: 299 forks

πŸ’» Programming Languages: Ruby - HTML - CSS - JavaScript

🏷️ Related Topics:
#ruby #rails #kanban #hotwire


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🧠 By: https://t.me/DataScienceM
πŸ”₯ Trending Repository: next-ai-draw-io

πŸ“ Description: A next.js web application that integrates AI capabilities with draw.io diagrams. This app allows you to create, modify, and enhance diagrams through natural language commands and AI-assisted visualization.

πŸ”— Repository URL: https://github.com/DayuanJiang/next-ai-draw-io

🌐 Website: https://next-ai-drawio.jiang.jp/

πŸ“– Readme: https://github.com/DayuanJiang/next-ai-draw-io#readme

πŸ“Š Statistics:
🌟 Stars: 3K stars
πŸ‘€ Watchers: 17
🍴 Forks: 375 forks

πŸ’» Programming Languages: TypeScript - CSS

🏷️ Related Topics: Not available

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🧠 By: https://t.me/DataScienceM
πŸ”₯ Trending Repository: Foundations-of-LLMs

πŸ“ Description: No description available

πŸ”— Repository URL: https://github.com/ZJU-LLMs/Foundations-of-LLMs

πŸ“– Readme: https://github.com/ZJU-LLMs/Foundations-of-LLMs#readme

πŸ“Š Statistics:
🌟 Stars: 13K stars
πŸ‘€ Watchers: 157
🍴 Forks: 1.2K forks

πŸ’» Programming Languages: Not available

🏷️ Related Topics: Not available

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🧠 By: https://t.me/DataScienceM
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πŸ”₯ Trending Repository: social-engineer-toolkit

πŸ“ Description: The Social-Engineer Toolkit (SET) repository from TrustedSec - All new versions of SET will be deployed here.

πŸ”— Repository URL: https://github.com/trustedsec/social-engineer-toolkit

πŸ“– Readme: https://github.com/trustedsec/social-engineer-toolkit#readme

πŸ“Š Statistics:
🌟 Stars: 13K stars
πŸ‘€ Watchers: 645
🍴 Forks: 3.1K forks

πŸ’» Programming Languages: Python - C++ - Shell - C - Java - CSS

🏷️ Related Topics: Not available

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🧠 By: https://t.me/DataScienceM
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πŸ”₯ Trending Repository: ML-For-Beginners

πŸ“ Description: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

πŸ”— Repository URL: https://github.com/microsoft/ML-For-Beginners

πŸ“– Readme: https://github.com/microsoft/ML-For-Beginners#readme

πŸ“Š Statistics:
🌟 Stars: 79.6K stars
πŸ‘€ Watchers: 1.1k
🍴 Forks: 18.5K forks

πŸ’» Programming Languages: Jupyter Notebook - HTML - Python - Vue - JavaScript - Dockerfile

🏷️ Related Topics:
#python #education #data_science #machine_learning #r #scikit_learn #machine_learning_algorithms #ml #machinelearning #machinelearning_python #scikit_learn_python #microsoft_for_beginners


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🧠 By: https://t.me/DataScienceM