Google Analytics 360 offers a way to be able to track website traffic and, by using its BigQuery integration, store the detail measures that may be useful from an analytical point of view.
Learn how to take the next steps into Infrastructure as Code, using python and Google's Cloud Deployment Manager....
During my time with an energy company, I worked in a team which had a set of unicorn fairy lights. Jokingly I suggested that they should have individual RGB LEDs which could tell the status of the app, the weather and...
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.
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?
Shine would like to invite you to a special event we are hosting in Melbourne on July 8.
In a one-off presentation to be held at ACMI in Federation Square, Shiners Graham Polley and Shane Neubauer will share with you the story of how they helped Telstra analyse massive data sets in a matter of seconds using the power of the cloud.