How Google does Machine Learning

What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to feature

Created by: Google Cloud Training

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Overall Score : 96 / 100

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Course Description

What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently -- of being about logic, rather than just data. We talk about why such a framing is useful for data scientists when thinking about building a pipeline of machine learning models. Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped. We end with a recognition of the biases that machine learning can amplify and how to recognize this.>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<

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Instructor Details

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The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an effective and impactful way. Google Cloud helps millions of organizations empower their employees, serve their customers, and build what's next for their businesses with innovative technology created in-and for-the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

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Reviews

4.8

499 total reviews

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By Serge H k on 2-May-18

Thes best course to turn machine learning into a service that reinvents companies

By Carlos G H on 30-Jun-18

The course was excellent. It cleared some myths about Machine Learning. I always though that training the ML model was important but collecting data is much more important than that.Looking forward to use Google Cloud Platform in the future for production of my projects.

By Juan S V on 2-Oct-18

Please explain the coding part

By Jimmy A on 19-Sep-18

The concept of this class is good, but the lad is out of date.

By RENATO U P on 15-Oct-18

Nice way to begin stuff! Hoping to see amazing stuff in upcoming courses of the specialization!

By Gokula K S on 6-Sep-18

A nice helicopter view of Google ML! some of the user interface is different with the one demonstrated in the videos but it's not a big problem.

By Sudhir T on 8-Aug-18

It's a good advertisement for Google products. As the start to a specialization in ML, it seems a little over-the-top with advertisement.

By Jimmy A on 6-Aug-18

Very exciting to be able to learn this directly from Google and get introduced to QwikLabs and Cloud Datalab... the process of accomplishing the labs does seem to be cumbersome, but perhaps the details will be explained later (how accounts are processed, APIs activated, credentials... how data and compute engines are kept on standby or persistent once setup...). I have had some difficulties with getting the labs to work at times... couldn't see the Webview widgets at one point, because I didn't realize that I had to close the menu bar on the left side of the screen.I have very much appreciated the overview introduction to the Google approach to ML... that is very helpful... knowing how to choose processes for ML and an appropriate approach to them... also keeping the scope of what they do somewhat limited and breaking it into pieces.Having some experience with SQL and Python are very helpful for completing the labs and while I have had some of both, my skills are rusty. I might go off and study both of those topics and then plan to come back to this course, but I will see how the next week goes. Thank you.

By Hsin-Jo T on 17-Jun-18

This was a good start for GCP with machine learning ,a relatively good course from the Googlers and very happy to be part of it .

By Saksham on 6-Nov-18

Great to know how to do machine learning in scale and to know the common pitfalls people may fall into while doing ML. Provides great hands-on training on GCP and get to know various API's GCP offers.

By Georgi S on 23-Dec-18

I wish there were more line by line code explanations of what we do in labs. That way it would be easier to experiment and create our own variations.

By Joachim H on 21-Dec-18

Nice course, but nothing impressive to be learned.