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Opiniones y comentarios de aprendices correspondientes a How Google does Machine Learning por parte de Google Cloud

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What are best practices for implementing machine learning on Google Cloud? What is Vertex AI and how can you use the platform to quickly build, train, and deploy AutoML machine learning models without writing a single line of code? What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently: it’s about providing a unified platform for managed datasets, a feature store, a way to build, train, and deploy machine learning models without writing a single line of code, providing the ability to label data, create Workbench notebooks using frameworks such as TensorFlow, SciKit Learn, Pytorch, R, and others. Our Vertex AI Platform also includes the ability to train custom models, build component pipelines, and perform both online and batch predictions. We also discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important to not skip the phases. We end with a recognition of the biases that machine learning can amplify and how to recognize them....

Principales reseñas


5 de nov. de 2018

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.


20 de mar. de 2019

Really easy with all instruction.I didnt feel bored at any point gave me the basic idea of what is machine learning and how easy google made API's and cloud platform for machine learning

Thank you

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26 - 50 de 1,098 revisiones para How Google does Machine Learning

por Javier G M

3 de ene. de 2021

This is basically a large ad of google.

por TODD L

23 de may. de 2019

This may be the most important Machine Learning course I've ever taken. This course is not about theory or technical details, this course is about how to get ML working for you in your business. Google shows us the business processes that they have used and helped other companies use to be successful in getting real value out of ML. If you have tried ML in your business and not gotten any traction, you may have fallen into some of the pitfalls discussed in this course. I look forward enthusiastically to following the recommendations in this course and championing them throughout my company. In this course Google shares real-world solid practical business experience on how to go about the end-to-end process to make profitable use of ML. I give this course my highest rating, 5 STARS!

por Ryan M

28 de oct. de 2019

Trying to run the Code from a local machine was a little more of a challenge than I thought it would be. Here's a code snippet that hopefully will help others in the future when they attempt to do the same.

#For this to work change __init__ in Programs\Python\Python37\Lib\site-packages\httplib2 line 1090 from int to float


# running Translate API

from googleapiclient.discovery import build

service = build('translate', 'v2', developerKey=APIKEY)

# use the service

inputs = ['I love words that aren\'t']

outputs = service.translations().list(source='en', target='fr', q=inputs).execute()

# print outputs

for input, output in zip(inputs, outputs['translations']):

print("{0} -> {1}".format(input, output['translatedText']))

por Martin L

19 de sep. de 2018

Very good course about production machine learning. I take this course after taking the Andrew Ng's course, as I found MatLab was not very popular among the community, and tried to learn some Tensorflow stuff. The first course in the specialization is a surprise. Very deep insight on machine learning in real world taught by Googlers. The serverless concept is also fascinating as I am facing issues with running ML stuff on my own. Recommended this course to people who wants to understand the design and business application part of ML.

por Billy A

1 de jun. de 2018

Invaluable introduction on PRACTICAL machine learning. The meat of this course is how to think about production ML services. If you are tired of endless algorithm design (or are less technically inclined), this course will introduce you to the mindset of thinking about problems from an ML (data) first perspective. The labs section at the end where you get to experiment with GCP felt a little rushed. I know it was just meant to be a teaser. Looking forward to going deeper in the next courses.

por Isaraparb L

31 de jul. de 2018

The course is good and very well depicted by the title "How Google does ML." You see a lot of real world examples/applications, obviously all provided by Google products. Moreover, they introduce a big picture of a machine learning project, and even more so a whole scheme of an organization that is about to do machine learning successfully. Videos are totally informative and concise, straight to the point without a lot of unnecessary "hello/welcome/thank you, etc." I like it!

por Vishal K

2 de jun. de 2018

Very nice introduction to Google Cloud Platform: Compute Engine, Storage, Data Lab, Big Query, Google's amazing ML APIs. I'm a novice and dont have much Technical background nor Data Science but this course was easy to follow.

Labwork was really inclusive as it contained some real-life scenarios and made me comfortable that with little practice (and little Tech expertise), I can also do ML/AI. Amazing course and a must do for anyone who is interested to learn and do ML

por Sarthak K

7 de may. de 2020

Having got to know about GCP again and it really makes a difference when you just work withuot cloud and with cloud . Many factors such efficiency, chances not to fail , total work on logics rather than building a pipeline that has been already made increases. However in my opinion one should take GCP fundamentals on data engineering course after this one or before this one and then jump to the next courses in this specialization.

Thank You Google

por Debayan C

13 de may. de 2020

This course is probably one of the finest curated introduction to an organizational ML solution standard.

We tend to overlook some of the critical phases and learning the processes and organizational know-how that GOOGLE applies to its ML solution development process would help me as an ML & AI engineer to not only revisit my skillset but also brush my application process for ease of deployment and for ensuring scalability within code .

por Sanjay S S G

19 de abr. de 2020

This course really helped me to understand How ML can really create a huge impact in the world of technology.The instructors were really interactive , they explain the concepts with real time application which i find it very interesting . I would like to thank the Google Cloud Team for creating this course and I'm looking forward to join your other courses and specialize in Machine Learning .

Thank You All

por Hussain W A

25 de jun. de 2020

I like this course but it is strictly teaching that the cloud to use it not the main ML into details. Like we know data they told to collect but we haven't performed any data handling or collecting exercise nor we have done any accuracy optimization. What we did just learnt how to use Google API's not what the inside code it so it's just marketing of google product which they are selling.

por Dhruv T

1 de abr. de 2019

First off all , Thank you Google for providing this course to me for free . It has helped to gain lot of knowledge . It could be a first step for me in learning about Ml . I request you to keep supporting me further . This is one of the finest course I have come across . I would give you a best result by participating in google summer of code and be a part of google one day

por Patrick M A

3 de jun. de 2018

I really liked this course because of it's business problem solving approach. It's not really about the technology itself, but about how to use it to solve problems, with many Google examples. The course does not only talk about machine learning models, but it also stresses out the importance of implementation in order to make the model useful for daily operations.

por Кирилл К

5 de may. de 2020

Perfect course for newbies as an intro to machine learning. By the way, the best part is, that you learn on real-world examples by executing code in the ai notebooks (GCP), diving deeper and deeper. I found this course useful, I get new knowledge of cloud services, and a general overview of how Google Cloud can be handy for me in my aspiring projects.


11 de jun. de 2018

Excellent course. The Lab also provided with step by step instructions to have a superb experience on Googles Cloud Platform (GCP) using various tools like DigiLab, BigQuery, ML API's for Images, Video & Audio etc. The instructors are also having indepth knowledge in the subject and provides suitable real life example for each items. Thank you

por khalil e

23 de ago. de 2018

I've been taking lots of ML courses this last year, and I was looking for a training that covers the strategy and steps towards building efficient ML models, and not only the algorithmic part of it ! Throughout this course, I've been able to discover the "realistic" picture of setting up ML in a company ! One of the best MOOCs in this subject

por Deleted A

12 de may. de 2020

Google gave me a new way to think about machine learning and how to construct the plan for the new ML projects. It's nice to see how ML is working in the production on google. I'm really impressed in the first week. I hope that I can finish this specialization. If anyone is looking for ML in production, this is the right place to start.

por 丸瀬重雄

7 de oct. de 2018

Good lesson taught regarding training bias. As machine learning becomes more and more dominant and influential in the cloud, we would like the predictions to be fair and square by all means, in terms of gender, nationality, etc. Several redundancies with similar courses on Coursera, but those are essential to this subject nonetheless.

por Royston D

28 de jun. de 2019

Some may argue the ending was a promotion of the cloud platform offerings,but I feel it was necessary to showcase that there exist continuously developed models by Google.

I can almost guarantee that a self developed model for the purpose of vision speech etc. will never perform as good as the one offered on the cloud platform.

por Sarath P V K

15 de jun. de 2020

Easy to understand and technologically apt course. Best for understanding the basics of ML and learning how Google incorporates ML in its products and services. Provides access to easily usable Google Cloud Platform for hands-on experience and a better understanding of the application and use of GCP and its capabilities.

por Danush V

3 de jun. de 2018

This course gave me a new perspective into Machine Learning solutions. I was focused on dataset and optimizing algorithms but then google helped me understand how serving ML solutions is the bigger picture and how google provides different solutions to help us in that cause. I look forward to complete this specialization

por Nadeem K

5 de ago. de 2018

Excellent course. Complex concepts were broken down into easy to understand language. Kudos to the Google team for helping me become more familiar with ML. Greatly appreciate it.

ML is my passion and I didn't know up until know that I can actually learn ML. Google Team made this possible. THANK YOU!!


por Ryan W

30 de jul. de 2018

This course contains some of the best information about Machine Learning in the business context that I've ever discovered.

I'm grateful to Google for making their hard-won insights available for such a low cost, even if a major part of their motivation is marketing GCP products. Truly excellent.

por Siddhant P

14 de ago. de 2019

This is the most essential course on how to get started with ML in the GCP. The course is neatly structured and the different parts are covered beautifully by the course instructors. The hands-on labs are amazing. Being familiar with Qwiklabs, I got through every assignment easily. Thank you.

por Fazeel H U

6 de ene. de 2020

A must-take course for the young engineers, entrepreneurs to build their projects easily quite efficiently. Don't waste time in training already built models just use them, make efforts in developing models which don't exist. Thank you, Google for creating such an amazing, engaging course.