Exploring the Fascinating World of Neural Network Architectures
Welcome to the comprehensive guide on neural network architectures. In this guide, we will dive into various architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers!
Contents
Convolutional Neural Networks (CNNs) 🐸
CNNs are primarily used for image processing. They consist of convolutional layers that detect patterns, making them highly effective for visual data.
Recurrent Neural Networks (RNNs) 🐸
RNNs are designed for sequence prediction tasks. They maintain a state vector to keep context about inputs observed so far, vital for time-series data.
Transformers 🐸
Transformers use attention mechanisms to process data sequences, enabling parallel processing and achieving state-of-the-art results in NLP tasks.