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

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30 NumPy MCQs with solutions

Are you ready??

Let's start: https://codeprogrammer.notion.site/30-NumPy-MCQs-with-solutions-23ccd3a4dba9803e8fafe39a110a3f9e?source=copy_link

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🔥 Master Vision Transformers with 65+ MCQs! 🔥

Are you preparing for AI interviews or want to test your knowledge in Vision Transformers (ViT)?

🧠 Dive into 65+ curated Multiple Choice Questions covering the fundamentals, architecture, training, and applications of ViT — all with answers!

🌐 Explore Now: https://hackmd.io/@husseinsheikho/vit-mcq

🔹 Table of Contents
Basic Concepts (Q1–Q15)
Architecture & Components (Q16–Q30)
Attention & Transformers (Q31–Q45)
Training & Optimization (Q46–Q55)
Advanced & Real-World Applications (Q56–Q65)
Answer Key & Explanations

#VisionTransformer #ViT #DeepLearning #ComputerVision #Transformers #AI #MachineLearning #MCQ #InterviewPrep

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🧹 ObjectClear — an AI-powered tool for removing objects from images effortlessly.

⚙️ What It Can Do:

🖼️ Upload any image
🎯 Select the object you want to remove
🌟 The model automatically erases the object and intelligently reconstructs the background

⚡️ Under the Hood:

— Uses Segment Anything (SAM) by Meta for object segmentation
— Leverages Inpaint-Anything for realistic background generation
— Works in your browser with an intuitive Gradio UI

✔️ Fully open-source and can be run locally.

📎 GitHub: https://github.com/zjx0101/ObjectClear

#AI #ImageEditing #ComputerVision #Gradio #OpenSource #Python

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🚀 Comprehensive Tutorial: Build a Folder Monitoring & Intruder Detection System in Python

In this comprehensive, step-by-step tutorial, you will learn how to build a real-time folder monitoring and intruder detection system using Python.

🔐 Your Goal:
Create a background program that:
- Monitors a specific folder on your computer.
- Instantly captures a photo using the webcam whenever someone opens that folder.
- Saves the photo with a timestamp in a secure folder.
- Runs automatically when Windows starts.
- Keeps running until you manually stop it (e.g., via Task Manager or a hotkey).

Read and get code: https://hackmd.io/@husseinsheikho/Build-a-Folder-Monitoring

#Python #Security #FolderMonitoring #IntruderDetection #OpenCV #FaceCapture #Automation #Windows #TaskScheduler #ComputerVision

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🚀 Comprehensive Guide: How to Prepare for an Image Processing Job Interview – 500 Most Common Interview Questions

Let's start: https://hackmd.io/@husseinsheikho/IP

#ImageProcessing #ComputerVision #OpenCV #Python #InterviewPrep #DigitalImageProcessing #MachineLearning #AI #SignalProcessing #ComputerGraphics

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A useful find on GitHub CheatSheets-for-Developers

LINK: https://github.com/crescentpartha/CheatSheets-for-Developers

This is a huge collection of cheat sheets for a wide variety of technologies:

JavaScript, Python, Git, Docker, SQL, Linux, Regex, and many others.

Conveniently structured — you can quickly find the topic you need.

Save it and use it 🔥

👉 @DATASCIENCEN

This repo is awesome. It features RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more.

✅ link: https://github.com/Shubhamsaboo/awesome-llm-apps

#RAG #AIAgents #MultiAgentSystems #VoiceAI #LLMApps

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500 Essential Web Scraping Interview Questions

Start: https://hackmd.io/@husseinsheikho/WS-Interview

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500 Essential Web Scraping Interview Questions with Answers - part 1 (1 to 238)

Link: https://hackmd.io/@husseinsheikho/WS-Ans238

500 Essential Web Scraping Interview Questions with Answers - part 2 (239 to 386)

Link: https://hackmd.io/@husseinsheikho/WS-Ans386

500 Essential Web Scraping Interview Questions with Answers - part 3 (387 to 500)

Link: https://hackmd.io/@husseinsheikho/WS-Ans500

https://t.me/DataScienceQ ✅

This repository contains a collection of everything needed to work with libraries related to AI and LLM.

More than 120 libraries, sorted by stages of LLM development:

→ Training, fine-tuning, and evaluation of LLM models
→ Integration and deployment of applications with LLM and RAG
→ Fast and scalable model launching
→ Working with data: extraction, structuring, and synthetic generation
→ Creating autonomous agents based on LLM
→ Prompt optimization and ensuring safe use in production

🌟 link: https://github.com/Shubhamsaboo/awesome-llm-apps

👉 @codeprogrammer