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.
Implementing TensorFlow in production
Understanding TensorFlow Hub
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...
