What is the difference between serialization and deserialization in C++ ML libraries?

What is the difference between serialization and deserialization in C++ ML libraries?

Serialization is the process of converting an object into a format that can be easily stored or transmitted, while deserialization is the reverse process, converting the stored format back into an object.

Can you give me an example of serialization in a C++ ML library?

Sure! In a C++ ML library, you might serialize a trained model to a file using a function like saveModel(), which writes the model's parameters to disk.

How does deserialization work when loading a model?

Deserialization involves reading the model file and reconstructing the model object in memory, often using a function like loadModel().

What formats are commonly used for serialization in C++?

Common formats include JSON, XML, and binary formats, depending on the library and the specific use case.