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Running a Neural Network Model in OpenCV

Many machine learning models have been developed, each with strengths and weaknesses. This catalog is not complete without neural network models. In OpenCV, you can use a neural network model developed using another framework. In this post, you will learn about the workflow of applying a neural network in OpenCV. Specifically, you will learn:

🏐 What OpenCV can use in its neural network model
🏐 How to prepare a neural network model for OpenCV

Read: https://machinelearningmastery.com/running-a-neural-network-model-in-opencv/

#NeuralNetworks #OpenCV #MachineLearning #AI #DeepLearning #ModelDeployment #ComputerVision #TechTutorials #DataScience #MLModels

https://t.me/CodeProgrammer
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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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🥇 This repo is like gold for every data scientist!

Just open your browser; a ton of interactive exercises and real experiences await you. Any question about statistics, probability, Python, or machine learning, you'll get the answer right there! With code, charts, even animations. This way, you don't waste time, and what you learn really sticks in your mind!

⬅️ Data science statistics and probability topics
⬅️ Clustering
⬅️ Principal Component Analysis (PCA)
⬅️ Bagging and Boosting techniques
⬅️ Linear regression
⬅️ Neural networks and more...


📂 Int Data Science Python Dash
🐱 GitHub-Repos

👉 @codeprogrammer

#Python #OpenCV #Automation #ML #AI #DEEPLEARNING #MACHINELEARNING #ComputerVision
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