Project Overview
Neural networks, inspired by the structure and function of the human brain, are a powerful class of machine learning algorithms capable of learning complex relationships between inputs and outputs. In the context of autonomous driving, neural networks can process vast amounts of raw data from various sensors and learn to recognize patterns, such as identifying objects, predicting trajectories, and making strategic driving decisions. Deep learning, a subset of neural networks, employs multiple layers of interconnected nodes to enable more advanced feature extraction and decision-making. By training on large datasets, neural networks allow autonomous vehicles to adapt and respond to diverse driving situations, leading to safer and more efficient navigation in real-world environments.