Chevron Left
Back to Serverless Machine Learning with Tensorflow on Google Cloud Platform

Learner Reviews & Feedback for Serverless Machine Learning with Tensorflow on Google Cloud Platform by Google Cloud

4.5
2,445 ratings
296 reviews

About the Course

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....

Top reviews

NP

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.

MG

Sep 21, 2017

Great course! I've learnt a lot. The concepts where super clear. The coding part was a little difficult, I didn't understand all af it, but it's good to have a complete example to use.

Filter by:

76 - 100 of 291 Reviews for Serverless Machine Learning with Tensorflow on Google Cloud Platform

By Felipe J C

Nov 06, 2018

bueno pero con detalles

By Cheuk M L

Nov 15, 2018

Super useful and it's showing the power of ML and how GCP can unleash the power of AI

By Mikhail M

Nov 18, 2018

Very useful!

By Charles B

Aug 05, 2018

Really nice introduction to ML. Thanks

By Ricardo M S

Jul 18, 2018

Excellent introduction to practical experimentation on the cloud.

By Mario F R O

Jul 21, 2018

This course is perfect to understand the principal components of TensorFlow, Recommended!

By 鈴木瑞人

Sep 18, 2018

Great Lecture!

By Brett W

Jul 25, 2018

Good introduction to ML, Tensorflow and Cloud ML

By Leandro M

Jul 29, 2018

I really enjoyed it! Even though I am not a data scientist, I could understand everything and increase my skiils!

By Alejandro J A

May 07, 2019

A very complete course.

By SATEESH K C

May 26, 2019

Easy way

By Monish K

May 27, 2019

This course was really good, too much informative and had a good learning curve

By Arjun S

Jun 17, 2019

Great Course!

By Egide

Jun 26, 2019

ML libraries, using data flow graphs to build models. helped me to create large-scale neural networks with many layers in the datalab.

By Thien A T

Jun 10, 2019

You will have good general knowledge about ML on Google Cloud and also have experimented through Lab course

By Kok S L

Jun 10, 2019

Very informative

By Gokula K S

Jul 17, 2019

Nice

By Narayanasamy K

Jul 28, 2019

The Data engineering specialization is really awesome. The concepts taught very precise,simple yet powerful. Enjoyed learning!! Thanks Google Engineering specialization team.

By Armando Q

Aug 05, 2019

Very excellent

By steve l

May 31, 2019

Interesting contents!! I learn a few new tricks.

By Navi T

May 18, 2019

Course is very good and detailed. It is really helpful.

By Suraj M

Jun 03, 2019

Got a good exposure

By Rômulo L V d S

Jun 03, 2019

Excellent course.

Great tools.

Many challenges for a data engineer.

By Vinoth K

Aug 09, 2019

Quite a lengthy course but worth it. Recommend to spend more time in labs and also when you have time work on the tools and have more knowledge on python.

By luân n

Aug 12, 2019

This course is difficult than previous course