Neural networks and deep learning are the backbone of modern artificial intelligence.
Each connection between neurons has a weight that determines its importance.
Training a deep neural network involves feeding it large amounts of labeled data and allowing it to adjust its parameters through multiple iterations.
Convolutional Neural Networks (CNNs) are a specialized type of deep learning architecture designed for image recognition, object detection, and computer vision tasks.
Recurrent Neural Networks (RNNs) are designed for tasks that involve sequential data, such as speech recognition, language modeling, and time-series forecasting.
Deep learning has become a driving force behind cutting-edge AI innovations, impacting nearly every industry.