Difference Between Perceptron, ANN and CNN for image classification
🎥 Perceptron vs ANN vs CNN | Image Classification Explained with Accuracy & Loss Comparison
In this video, I explain the difference between:
🧠 Perceptron
🧠 ANN (Artificial Neural Network)
🧠 CNN (Convolutional Neural Network)
using a real image classification project on the MNIST dataset.
You’ll see:
📊 Training Accuracy vs Applied (Test) Accuracy
📉 Training Loss vs Applied (Test) Loss
📈 Why CNN performs best on image data
🧩 How spatial features like edges and shapes matter in deep learning
This project shows clearly how:
• Perceptron is too simple for images
• ANN is better but still limited
• CNN is the best choice for image classification tasks
💻 Project Topics Covered
• Image Classification with MNIST
• Perceptron vs ANN vs CNN
• Deep Learning Basics
• Model Evaluation using Accuracy & Loss
• Training vs Testing Performance
🎯 Who is this video for?
• Students learning Machine Learning / Deep Learning
• Beginners in AI & Computer Vision
• Anyone curious about how CNN really works
📌 Project Source Code & README
https://github.com/shivam-prajapat/Percept...
🙏 Feedback is welcome — drop your thoughts in the comments!
Let’s learn, build, and grow together 🚀
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