GCP Tag

As a co-organizer for GDG Cloud Melbourne, I was recently invited to the Google Cloud Developer Community conference in Sunnyvale, California. It covered meetup organization strategies and product roadmaps, and was also a great opportunity to network with fellow organizers and Google Developer Experts (GDEs) from around the world.  Attending were 68 community organizers, 50 GDEs and 9 open source contributors from a total of 37 countries. I would have to say it was the most social conference I have ever attended. There were a lot of opportunities to meet with people from a wide range of backgrounds. I also got many valuable insights into how I could better run our meetup and better make use of Google products. In this post I'll talk about what we got up to over the two days.

Intro

Recommendation systems are found under the hood of many popular services and websites. The e-commerce and retail industry use them to increase their sales, the music services provide interesting songs to their listeners, and the news sites rank the daily articles based on their readers interests. If you really think about it, recommendation systems can be used in pretty much every area of daily life. For example, why not automatically recommend better choices to house investors, guide your friends in your hometown without you being around, or suggest which company to apply to if you are looking for a job.

All pretty cool stuff, right!

But, recommendation systems need to be a lot smarter than a plain old vanilla software. In fact, the engine is made up of multiple machine learning modules that aim to rank the items of the interests for the users based on the users preferences and items properties.

In this blog series, you will gain some insight on how recommendation systems work, how you can harness Google Cloud Platform for scalable systems, and the architecture we used when implementing our music recommendation engine on the cloud. This first post will be a light introduction to the overall system, and my follow up articles will subsequently deep dive into each of the machine learning modules, and the tech that powers them.

Last week I had the privilege of attending Google Cloud Next in San Francisco. With Google finally due to open a datacenter in Australia this year, it was certain to be a great opportunity to learn about what's next with Google Cloud. From the moment I arrived at the baggage carousel at San Francisco International Airport, I was swamped with advertising for the conference. It was clear that Google is really pushing their cloud platform to as many developers as possible. This left me really excited for what was about to come over the following week. In this post I'm going to try and sum up how it all went.
tel-high-res Shine's Technical Excellence Leadership Group (TEL) has had a stellar year! In this post we've pulled together our top picks from 2016 that we think deserve a special shout out before the year comes to a close. But first, a quick recap on what the TEL group actually is. TEL was established in 2011 with the aim of publicising the great technical work that Shine does, and to raise the company's profile as a technical thought-leader through blogs, local meet up talks, and conference presentations. TEL is allocated a yearly budget from the super-duper generous Shine directors, and the members of the TEL group are put in charge of overseeing how it is spent. The budget comprises two parts: money and time. The monetary portion of the budget goes to prizes and bonuses for producing material. The time portion is for staff to draw upon to get away from their day-to-day work commitments and to produce their material. So, now that you know what TEL is all about, let's have a look at the highlight reel from 2016 shall we?