Takeaway points from GCPNext 2016

I recently attended GCPNext in San Francisco, where Google announced some of their latest stuff around Google Cloud Platform. One of the things that struck me the most from the conference was that Google is now focusing on its strengths in certain niche areas to carve out its own identity in the public cloud and win developer mindshare. Two areas were repeatedly stressed and they were the Google Cloud Data Platform and Machine Learning.

Google Cloud Data Platform provides an amazing fully-managed infrastructure to deal with your Big Data projects. BigQuery and Dataflow are its jewels there and if you have not used it, you owe yourself one. As an example, check out Google Developer Expert Graham Polley‘s recent article on “Creating a Serverless ETL Nirvana using Google BigQuery

Machine Learning was also big at GCPNext and given the vast amount of data that Google possesses over the last decade and more, it should come as no surprise that some of its machine learning models will be the most accurate for a wide range of use cases. What is interesting to see is that while it provides a platform for everyone to use , Tensorflow — it is also in the process of releasing ready to use APIs that tap into their powerful machine learning models at the backend. Machine Learning is not everyone’s cup of tea and most of us, having an API access to Machine Learning models will give us a huge jumpstart into making our applications smarter and address use cases that were previously almost impossible to solve.

One such API that it has released is Google Cloud Vision API that almost gives human eyes to your applications. It is a fairly capable API that provides label detection, safe search, logo detection OCR, landmark detection for your images. In many cases, the results are almost like magic. If you are looking to getting started with Google Cloud Vision API, try out the tutorial “How To Build a Monitoring Application using Google Cloud Vision API” that I recently published at ProgrammableWeb.

As part of its Machine Learning push, Google also announced a Machine Learning Platform and a Speech API, both of which are currently available only in Limited Preview.

Google also setup codelabs, where attendees could try out multiple features on Google Cloud Platform. You have full access to these codelabs. Try them now.

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