Using C++ in Data Science

C++ is widely used in many fields, including data science. Data scientists typically choose Python because of its simplicity and breadth of libraries, but C++ offers some advantages that make it an effective tool for data analysis. This chapter explains why C++ can be used in the data science industry and how it makes it possible. C++ is fast and efficient. In C++, code is compiled into machine code before execution. This compilation enables C++ programs to execute significantly faster than an interpreted language such as Python. C++ can perform well when dealing with extensive data or computationally intensive tasks. C++ algorithms can use lower memory management and better code execution to process data faster.

Additionally, C++ provides extensive support for parallel computing. The language offers libraries such as OpenMP and MPI, allowing developers to standardize their code and use multicore processors and distributed systems. Parallel computing is...