Computational Graphs
A computational graph is a way to represent mathematical operations as a directed graph, where nodes are operations (like addition or multiplication) or variables, and edges represent the flow of data. This structure visualizes how inputs are transformed into outputs and is crucial for understanding how gradients (the rate of change) propagate through complex models like neural networks during training. It underpins automatic differentiation.
Think of it as a detailed recipe flowchart, showing each step and ingredient passing from one process to the next.
Computational graphs are the bedrock of modern deep learning frameworks, enabling efficient calculation of gradients for model training and optimization.
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