Deep Learning

Deep learning is a subset of machine learning that involves training artificial neural networks to perform complex tasks such as image recognition, natural language processing, and speech recognition. The key difference between deep learning and traditional machine learning is that deep learning algorithms can automatically learn features from raw data without human intervention.

Artificial Neural Networks

Artificial neural networks (ANNs) are the fundamental building blocks of deep learning. They are composed of layers of interconnected nodes (also known as neurons) that process information. Each neuron in the network receives input signals from the previous layer, performs a computation, and passes the output signal to the next layer.

Convolutional Neural Networks

Convolutional neural networks (CNNs) are a type of neural network commonly used for image and video recognition tasks. CNNs are inspired by the organization of the visual cortex in animals and use a series of convolutional and pooling layers to extract features from the input image.

Recurrent Neural Networks

Recurrent neural networks (RNNs) are a type of neural network commonly used for natural language processing and speech recognition tasks. RNNs are designed to process sequential data by maintaining a hidden state that captures information about the previous inputs.