Convolutional 🧠 NN that recognizes patterns in images for tasks like Image recognition and Facial recognition.
Notes
Info
A convolutional neural network is a class of Deep Learning neural networks, most commonly used in computer vision applications.
TakeAways
- 📌 CNNs use convolutional layers to extract features from images
- 💡 The architecture consists of convolutional and pooling layers followed by fully connected layers
- 🔍 Widely used in object detection, image segmentation, and other computer vision tasks
- 🏛️ Introduced in the early 1980s, but popularized by Alex Krizhevsky’s winning entry for ImageNet challenge in 2012
Process
- 📝 Load and preprocess images
- 🛠️ Define CNN architecture with convolutional/pooling layers
- 🏋️ Train the Ml Model using appropriate optimizer and loss function
- ⚡ Model performance should be evaluated then on test set or validation data
Thoughts
- 🐝 Computational Efficiency: CNN’s reduce computational requirements by learning hierarchical features
- ⏳ Training Time: CNNs can take considerable time to train, especially for large datasets and complex architectures