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Volver a Serverless Machine Learning with Tensorflow on Google Cloud Platform

Opiniones y comentarios de aprendices correspondientes a Serverless Machine Learning with Tensorflow on Google Cloud Platform por parte de Google Cloud

2,441 calificaciones
296 revisiones

Acerca del Curso

This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: ● Identify use cases for machine learning ● Build an ML model using TensorFlow ● Build scalable, deployable ML models using Cloud ML ● Know the importance of preprocessing and combining features ● Incorporate advanced ML concepts into their models ● Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience ● Basic proficiency with common query language such as SQL ● Experience with data modeling, extract, transform, load activities ● Developing applications using a common programming language such Python ● Familiarity with Machine Learning and/or statistics Google Account Notes: • Google services are currently unavailable in China....

Principales revisiones


Jan 09, 2018

Thank you very much for making this course available on Coursera, I cannot agree more the knowledge of Mr Venkat. This is a great way to help people to get started with Google Machine Learning.


Sep 08, 2018

A very good course on TensorFlow, ML and Google MLE on GCP.\n\nThe Labs are self contained and the problems proposed are very challenging. I learned a lot on this course.\n\nThank you!

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151 - 175 de 290 revisiones para Serverless Machine Learning with Tensorflow on Google Cloud Platform

por Syed M H J

Mar 11, 2019

Very quick and short introduction to machine learning. Should have been a bit longer. Understanding written code is easy. Courses should ask the students to write their own code as well. Otherwise 5/5 course~!!

por Tom M

Feb 18, 2018

Great TensorFlow Examples

por Irfan U

Jun 15, 2018

Need to time for qwiklab test as it sometimes takes longer to execute certain part of the jupyter notebooks.

por Alexey I

Nov 24, 2017

Why would you cut videos in so many pieces? So many videos are under 1 minute...

por Edward C

May 05, 2018

The instructor and course content are good, though there are still some errors in the labs that need fixing.

por Jonathan G

Oct 24, 2017

A lot of detail to absorb in a short time.

por Ramesh R

Jul 17, 2017

Little difficult to follow but worth watching. If videos length being clubbed in a single video would be good. Lot of time for switching between videos

por Antonio O

Jun 29, 2017

very helpful. Have now a better perspective on GCP and ML Engine.

por Dominik M

Jul 21, 2017

Very informative, but some materials seem to be preapred chaotically, the videos' content is doubled and the modules are split into segments that are too short.

por Bruno M

Apr 23, 2018

Could be more interesting with done for more problems and examples

por Aussie P

Sep 26, 2017

(+) Great video content, great hands-on exercises. To make full benefit of the hands-on exercises, I highly suggest that you try to hand-code all of the codes in the Jupyter notebook. This helps you to internalize and force you to think about what is really happening. As you do this, do side searches whenever you encounter concepts / terminologies that are foreign

(-) The structuring of video content is messy! There are many videos that are just a few seconds or being repeated. This cause a lot of overhead time wasted in loading the sections. Please group some of contents together.

por Moses O M

Oct 24, 2017

Great Course!

It was easy to follow through the concepts and finally put everything together. The concepts were a bit complex, but Lak managed to break them down into comprehensible chunks. Some videos were very short and could benefit from combining them into at least 1 minute or a few minutes.

Overall great course and great delivery!

por Chirag A

Jul 31, 2017

Starting from basics of Tensorflow and going deep with low level apis, and finally teaching how to write code at scale and deploy in real use cases.

por Jon K

Sep 15, 2017

The lab breakdown was a little confusing, doing only certain parts of it, but still pretty informative. A couple of sections were complete overlap of the video from the previous section. Tons to learn here.

por Rahul K

Jul 31, 2017

Pretty good content and relevant for someone trying to understand Google offerings in this space.

por yinxi z

Dec 08, 2017

Thanks to the instructor! Great course, relevant materials and clear explanations. Just one suggestion, some videos are less than 1 min and seem to be cut off from the next ones, making the learning process a little interrupted.

por Stephen N

Nov 03, 2017

The labs would be more effective if we were forced to write code ourselves instead of just running completed pipelines.

por Olivia M R

Aug 10, 2017

It is a great overview of ML and Tensorflow given by to my opinion a great teacher like Lak!

However for newbies like me is was hard at points and frustrating times with codlabs and deprecated versions of packages.

Other than that, very nice course!

por Manuel P Z

May 15, 2018

Great introduction to tensor flow and machine learning techniques like feature engineering and hyperparameter.

por Narasimharao K

Jul 06, 2017

Some of the videos are repetitive but the content is very good. The Problem used for explaining the Tensorflow is great

por Jose A G

Sep 23, 2017

The teacher is good. He knows what he is teaching and is exhaustive in his topic teaching. I learned a few new tips and overview I didn't know before about Cloud ML workflow. Definitely useful. However, I think that it was very exhaustive and I felt like learning this topic needs a tremendous amount of knowledge. Some topics I did not quite understand, specifically learning Tensorflow and cloud ML commands and code, e.g how to get the models into Cloud storage, how to train models, how to preprocess data and load data into Tensorflow, etc. These topics were explained through code (and in words briefly afterwards) and there was no documentation about what the code does, returns, is for, etc. For this reason, I felt overwhelmed (I had to check what each and every function does, in some cases I just assumed what it did), and stricken by the amount of code and knowledge required to set up a Tensorflow-Cloud ML workflow. Definitely Intermediate to expert level work. I would reckon that if you would like to really learn Tensorflow-CloudML-BigQuery-Cloud Storage workflow, to go to a course where you actually complete a project yourself, and the teacher covers the coding aspect of this topic from scratch and in worthy amount of depth. This course is definitely a verbal overview, somewhat of a showcase, of what is possible with Cloud ML, and is does not cover the coding aspect of it. In this course the project (taxi cab ride fare estimation) is already completed for you. In the end the lab is touted to be completable in a week, however it took me 1.5 weeks to complete it, and more time to complete a new project.

por francisco q

Sep 03, 2017

I found this course the heaviest in terms of content. There was a lot to grasp and I had to take a few breaks. It was quite useful for getting a better understanding of Machine Learning and where TensorFlow fits in the Google Stack.

My recommendations is to spend more time on the TensorFlow lab review section is it it was quite short and subject was the most difficult to understand. I had to re-read the code several times and do some short modifications to understand the basics.

I think it is a good course but I did not have a strong understanding of TensorFlow just for the lectures and labs. I had to play around for at least 2 hours with TF before I understood the concepts explained in the course.

por Girish P

Dec 13, 2017


por C L G

Jan 19, 2018

The scope is ambitious - but the area is complex so it needs to be.

The concepts are presented clearly, but the code and techniques will take more study than the course allows.

A good grounding in Python certainly helps.

por Amit K

May 30, 2018

need more details on TensorFlow and Nueral networks, will have to get that outside now