Convolutional Neural Networks (CNNs)

Summary

A network architecture specialized for image data — convolutional layers detect local patterns (edges, textures) that combine into higher-level features as you go deeper into the network.

How to Learn This

1Read a visual explainer of how a convolution operation slides over an image.
2Build a simple CNN for image classification on a small dataset (e.g. MNIST).
3Learn the roles of pooling layers and why they reduce spatial dimensions.

Building Networks With PyTorch

Recurrent Neural Networks (RNNs) & LSTMs

More topics in Deep Learning Fundamentals

Neural Network Basics Activation Functions Backpropagation & Gradient Descent Building Networks With TensorFlow / Keras Building Networks With PyTorch Recurrent Neural Networks (RNNs) & LSTMs Transfer Learning Regularization in Deep Learning (Dropout, Batch Norm)GPUs & Training Basics

Stuck on this topic? Ask an Insider

Get 1:1 guidance from people who've walked this exact path — free on the InsideEdge app.

Download