Google cloud and varied services provided on top of it are very confusing to comprehend. It’s not just with google but you can visit AWS and azure, it’s very confusion, rather I would say, since each cloud provided is using their own nomenclature for their services, it becomes difficult to remember what does what. Of course once you start using it, it will become natural to you but when you are getting started, this is frustrating. I have just completed a course How Google does Machine Learning so I thought let me make very simple note for myself and for other to keep track of it.
There are many services which are offered by Google but for beginners everything is not needed to get started, so I will split this post in two parts.
Part-1 : Getting started
Google Cloud Platform is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.
Compute Engine – Infrastructure as a Service to run Microsoft Windows and Linux virtual machines.
App Engine – Platform as a Service to deploy Java, PHP, Node.js, Python, C#, .Net, Ruby and Go applications.
Cloud Storage – Object storage with integrated edge caching to store unstructured data.
Cloud Datalab – Tool for data exploration, analysis, visualization and machine learning. This is fully managed Jupyter Notebook service.
BigQuery – Scalable, managed enterprise data warehouse for analytics.
Cloud Natural Language – Text analysis service based on Google Deep Learning models.
Cloud Speech-to-Text – Speech to text conversion service based on machine learning.
Cloud Text-to-Speech – Text to speech conversion service based on machine learning.
Cloud Translation API – Service to dynamically translate between thousands of available language pairs
Cloud Vision API – Image analysis service based on machine learning
Cloud Video Intelligence API– Search and discover your media content with Cloud Video Intelligence