What is the purpose of compiling a model in TensorFlow?
The purpose of compiling a model in TensorFlow is to convert the high-level, human-readable code written by the developer into a low-level representation that can be efficiently executed by the underlying hardware. This process involves several important steps and optimizations that contribute to the overall performance and efficiency of the model. Firstly, the compilation process
How is the model compiled and trained in TensorFlow.js, and what is the role of the categorical cross-entropy loss function?
In TensorFlow.js, the process of compiling and training a model involves several steps that are crucial for building a neural network capable of performing classification tasks. This answer aims to provide a detailed and comprehensive explanation of these steps, emphasizing the role of the categorical cross-entropy loss function. Firstly, to build a neural network model