Artificial Intelligence and Machine Learning


Course Introduction
What is GCP?
Course Conclusion
2m 38s
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In this course, we will take a virtual tour of the main offerings of Google Cloud Platform Services. 

Learning Objectives

  • Compute
  • Storage
  • Networking
  • Artificial Intelligence and Machine Learning
  • Security and Operations

Intended Audience

  • Anyone who wants to learn about the main services available on Google Cloud Platform


  • Basic understanding of computers, servers, and data centers
  • Basic understanding of cloud principles

In this lesson, I want to talk about some of the most exciting services in GCP: that is Artificial Intelligence and Machine Learning.  Google is known for being on the cutting edge of this space.  The world was shocked when its AlphaGo software defeated one of the best human players of the board game, Go.

For those who don’t already know, Artificial intelligence (usually abbreviated as AI) is a field of study that attempts to give machines the same level of intelligence that humans possess.  Essentially, the goal of AI is to create machines that are capable of acting on their own, without direct human intervention.  Now AI is sort of a wider field of study, where Machine Learning (or ML) is a specific branch in that field.  Machine learning is mostly focused on developing systems that can learn.  Now by “learn”, I mean that they use large amounts of data to slowly improve their responses.

Currently, Google divides its AI and ML services into four categories: Sight, Language, Conversation, and Structured Data.

Under Sight, they have services like the Vision API, which can detect objects, faces, and text in images.  The Video Intelligence API recognizes objects, places, and actions in video.  Document AI uses machine learning to help you parse and identify data inside your documents, such as company names, addresses, and phone numbers.

Under Language, they have the Translation API, which can convert text from one language to another.  It currently supports over one hundred different languages.  They also have the Natural Language API, which performs tasks like sentiment analysis.  For example, it can classify a message as being either positive, negative, or neutral.

The Conversation category includes the Text-to-Speech and Speech-to-Text APIs, which do exactly what you would expect.  It also includes a service called DialogFlow, which can generate realistic sounding dialogue.  Using DialogFlow, you can build chatbots and voicebots to handle things like customer support requests.

The last category is Structured Data. These services allow you to feed in structured data and get back insights.  For example, the Recommendations AI can look at a customer’s previous purchases and recommend other products that they might be interested in buying.  Also, Cloud Talent Solutions can automatically detect and understand job content and applicant intent. Candidates can quickly find the most appropriate jobs, while companies can identify, attract and hire quality candidates.

All of these prebuilt AI services have been trained based on general sets of data, so they might not be able to handle your specific needs. Now for these scenarios, Google provides its AutoML suite of services. For example, you might need to identify product defects in your factory assembly lines.  By feeding your own data into AutoML Vision, you can train a custom model without having to know machine learning.

If you need to build custom models that are outside the scope of the AutoML suite, then you can use Vertex AI (which was previously named the AI Platform suite).  It includes many different services, but the most important ones are AI Platform Training and AI Platform Prediction. The Training service lets you train custom models using popular Python-based frameworks.  Or you can also access a repository of plug-and-play AI components (including end-to-end AI pipelines and out-of-the-box algorithms) by using AI Hub.

Alright, so let’s review all the AI and ML services I just talked about.  Remember, you got the four main categories:

  • Sight services, including the Vision API, Document API, and Video Intelligence API
  • Language services, including the Translation API and Natural Language API
  • Conversation services, include Text-to-Speech, Speech-to-Text and DialogFlow
  • Structured Data services, including Recommendations AI and Talent Solutions

Now, remember, if the standard APIs are not enough, you can also train your own models using AutoML.  And you can access AI Hub for plug-and-play AI components as well. And that should cover the main AI & ML services on GCP.


About the Author
Learning Paths

Daniel began his career as a Software Engineer, focusing mostly on web and mobile development. After twenty years of dealing with insufficient training and fragmented documentation, he decided to use his extensive experience to help the next generation of engineers.

Daniel has spent his most recent years designing and running technical classes for both Amazon and Microsoft. Today at Cloud Academy, he is working on building out an extensive Google Cloud training library.

When he isn’t working or tinkering in his home lab, Daniel enjoys BBQing, target shooting, and watching classic movies.

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