rushilgupta

Intro

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.

What is a tensor?

rushilgupta

INTRO

Concurrency is a domain I have wanted to explore for a long time because the locks and the race conditions have always intimidated me. I recall somebody suggesting concurrency patterns in golang because they said "you share the data and not the variables".

Amused by that, I searched for "concurrency in golang" and bumped into this awesome slide by Rob Pike: https://talks.golang.org/2012/waza.slide#1 which does a great job of explaining channels, concurrency patterns and a mini-architecture of load-balancer (also explains the above one-liner).

Let's dig in:

Goroutines