Understanding Google Cloud’s Machine Learning API’s .

Aryendra Prakash Singh
4 min readMay 2, 2020

Google Cloud is a platform that consists of almost more than 250 API’s. Phenomenal , isn’t it? Well, I think that too,Yes it is,Lets find out why?

A whole platform that consists of the most prominent technologies and many types of tools to make things simple and simpler,the cloud is basically a provider of computing resources for running applications and operating systems.Since its an infrastructure which itself is responsible for hosting and storing all other major products and their infrastructures,it is a monopoly and a masterpiece .

What are API’s ?

Application Programming Interfaces, which is a software intermediary that allows two applications to talk to each other. Each time you use an app like Facebook to send an instant message, or check the weather on your phone, you’re using an API. In a simple language,we can always say that its a connection or a bridge between the application and a user.

Machines…..Are they Learning?

  • Machine Learning provides systems the ability to automatically learn and improve from experience .
  • It learns from examples and experiences.
  • Fast, scalable, and easy-to-use AI offerings including machine learning, video and image analysis, speech recognition, and multi-language processing.These are some of its examples.

Well,I’m not a machine learning expert that’s the reason I’ll rather avoid talking something too technical about it,but that’s all for basic ML in GCP by my view.

Cloud Machine Learning API’s

  • They are certain API’s in Google Cloud which are specifically built to make your machine work on the basis of the specifics that are expected .
  • Wanna know about details of an image, video, speech etc.?(It helps in giving detailed description of the content)
  • Specific API’s are there for every specific domain(genre).

Let’s discuss few of the most prominent ones.

Natural Language API

Natural Language API uses machine learning to reveal the structure and meaning of text.Its pre-trained models deliver language understanding features, including content classification and sentiment, entity, and syntax analysis.It gives us the detailed information about the text and also shows the prediction percentage for that.

A demo of Natural Language API

Speech-to-Text API

speech-to-text API

Cloud Speech-to-Text enables us to convert audio to text by applying neural network models in an API. You can enable voice command-and-control, transcribe audio from call centers, and more. It can process real-time streaming or prerecorded audio, using Google’s machine learning technology.It has a set of almost 120+ languages .Also,its Auto Detect Language Feature is a great boon.It is used mostly in many of the products these days like, smart speakers,virtual assistants,Google maps,smart audio systems etc.

Video Intelligence API

Detecting anything with detailed analysis in a running video is quiet cool, right?

Video Intelligence API’s pre-trained models extract metadata, identify key nouns, and annotate video content. AutoML Video Intelligence lets you train custom models for projects that aren’t covered by the pre-trained API. And try both products together for the most sophisticated results.

Cloud Vision API

Google Cloud has a really powerful API named as Vision ,it not only detects objects and elements but also gives. Its powerful pre-trained Vision API models quickly classify images into thousands of categories (such as “sailboat” or “Eiffel Tower”) and recognize individual objects, faces, and words.

Cloud Vision Demo

Well,this was a roundup of the most popular Machine Learning APIs of Google Cloud,they are, in some terms, really efficient and precise . The prediction and its calculations are most of the time accurate and real.These kind of APIs are in our daily usage somewhere or other and sometimes we are able to relate but sometimes we can’t.Google Cloud has a very essential role in its own as its the infrastructure that is holding these kind-of essential APIs which are playing an important role in multiple number of really large products.

Aryendra Prakash Singh

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Aryendra Prakash Singh

Designer | Developer | Video Editor | Web | Product Enthusiast | DSC Core | Speaker LinkedIn : linkedin.com/in/hashtagaps Twitter : twitter.com/hashtagaps