TensorFlow’s APIs: A match made in machine learning heaven

TensorFlow is a machine learning framework which provides a wide range of APIs for building and training machine learning models. These APIs are divided into several categories:

Low-level APIs: These APIs provide a low-level interface to TensorFlow and allow you to build custom machine learning models from scratch. They include the TensorFlow Core API and the TensorFlow Eager API.

High-level APIs: These APIs provide a higher-level interface to TensorFlow and allow you to build machine learning models using pre-built and optimized components. They include the TensorFlow Estimators API, the TensorFlow Keras API, and the TensorFlow Lite API.

Data APIs: These APIs provide functions for loading, processing, and manipulating data for machine learning. They include the TensorFlow Datasets API and the TensorFlow IO API.

Model serving APIs: These APIs provide functions for deploying machine learning models for serving and inference. They include the TensorFlow Serving API and the TensorFlow Lite API.

Other APIs: TensorFlow also provides a number of other APIs for tasks such as visualization and debugging, as well as APIs for working with specific types of data such as text and images.

TensorFlow closely resembles a Python package, and it shares many of Python’s features. However, TensorFlow’s core features a distributed runtime. Python is one of the many languages that can achieve this capability.

C API for TensorFlow:

Only the C and Python APIs are supported by TensorFlow officially (some parts). C APIs should be used whenever we are about to make TensorFlow API for some other languages, as lots of languages have ways to connect with C language.

API for TensorFlow in C++:

TensorFlow’s runtime is written in C++, and most of the time, TensorFlow and C++ are coupled via header files. Although the C++ API is still in its experimental stages of development, Google has committed to using C++.

A TensorFlow R API:

There are various methods used to provide API support in the R API for TensorFlow created by RStudio. In contrast to TensorFlow, the R API includes the Python API in its entirety. However, R users have full access to the Python API’s functionalities.