When it comes to software engineering, we see several best practices, like version control through GitHub, reusable libraries, continuous integration, and others, which have made developers more productive. Machine learning is a new field where there is a definite need for some tooling to make model deployment simple and improve a data scientist's productivity. In that respect, TensorFlow has released a host of tools recently.
Software repositories have a real benefit in the field of software engineering as they enhance the reusability of code. This not only helps to improve developer productivity, but also helps in sharing expertise among different developers. Also, because developers now want to share their code, they develop their code in a manner that is more clean and modular so that it can benefit the entire community.
Google introduced TensorFlow Hub to achieve the similar purpose of reusability in machine learning. It...