Neural networks have been a cornerstone in the field of artificial intelligence, enabling machines to perform complex tasks with high accuracy. This tutorial will introduce you to various neural network architectures and their applications.
Overview of Neural Network Architectures
Feedforward Neural Networks: The simplest type of neural network, where the data moves in only one direction.
- Feedforward Neural Network
Convolutional Neural Networks (CNNs): Designed for analyzing visual imagery, CNNs have been highly successful in image recognition tasks.
- Convolutional Neural Network
Recurrent Neural Networks (RNNs): Suited for sequential data like time series or natural language processing.
- Recurrent Neural Network
Generative Adversarial Networks (GANs): Consist of two neural networks, a generator and a discriminator, competing against each other.
- Generative Adversarial Network
Transformers: Used extensively in natural language processing tasks, transformers have become the state-of-the-art models for many NLP tasks.
- Transformer
Learn More
To delve deeper into neural network architectures, you can explore our comprehensive tutorials on neural network basics.