There is a lot of buzz around neural-nets and how cool they are for image-recognition and text-recognition. There are a lot of sources out there to learn tensorflow and their application to solve these set of problems.
I'd reommend a course offered by Google on Udacity which teaches all about this stuff: https://classroom.udacity.com/courses/ud730.
This course doesn't cover the details of mathematics behind neural-nets and so doesn't this gist. However, the instructors do go into the intuition, breaking down a complex problem like visual recognition into abstract concepts and writing a program to predict some tensors and ultimately those concepts.
Through this gist I've tried to cover a very basic introduction to the tensorflow framework, the data structures it uses and it's application in a predictive-text model.