TensorFlow has become a popular choice for developers working on machine learning and deep learning projects, offering a powerful framework for building and training models. While commonly associated with Python, TensorFlow also provides support for C++, allowing developers to leverage its capabilities in a C++ environment. In this article, we will explore the fundamentals of TensorFlow for C++ developers, from setting up the environment to building, training, and integrating models into C++ applications. By understanding the key features, best practices, and optimization techniques, C++ developers can harness the full potential of TensorFlow in their projects.