TensorFlow Guide: Core Concepts - Tensors, Operations, and Graphs

Sun, 26 Oct 2025 00:00:00 +0000

2. Core Concepts and Fundamentals

TensorFlow is built upon a few fundamental concepts that, once understood, unlock its full power. In this chapter, we’ll break down the core building blocks: Tensors, Operations, and the underlying concept of Graphs (even in TensorFlow 2.x’s eager execution model).

2.1 Tensors: The Universal Data Structure

In TensorFlow, all data—whether it’s raw input, model weights, biases, or outputs—is represented as tensors. A tensor is a multi-dimensional array, similar to NumPy arrays, but with the added benefit of being able to run on GPUs (for accelerated computation) and being part of a computation graph.

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TensorFlow Guide: Core Concepts - Tensors, Operations, and Graphs

2. Core Concepts and Fundamentals

2.1 Tensors: The Universal Data Structure