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How Google does Machine Learning(으)로 돌아가기

Google 클라우드의 How Google does Machine Learning 학습자 리뷰 및 피드백

4.6
별점
6,948개의 평가
1,095개의 리뷰

강좌 소개

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....

최상위 리뷰

JT

2018년 11월 5일

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.

PB

2019년 3월 20일

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\n\nThank you

필터링 기준:

How Google does Machine Learning의 1,086개 리뷰 중 326~350

교육 기관: Manish K

2019년 8월 16일

very interesting and new topics for me, learned a lot from that.

교육 기관: Praveen k

2018년 11월 12일

Awesome course to start with ML and hands on GoogleCloudPlatform

교육 기관: Sabestin N

2020년 7월 14일

Thank you so much for giving good exposure of machine learning.

교육 기관: 김용완[YongWan K

2019년 10월 20일

Very good understandable and easy to use something tools

Perfect

교육 기관: Taggart J

2019년 7월 17일

Way more interesting and useful than I expected an intro to be.

교육 기관: Sumit k Y

2019년 5월 13일

Great things to learn. Pretty well organized.

Thank you Googlers

교육 기관: Abhinav S

2018년 7월 30일

This was a great introduction to using GCP for ML. I loved it!!

교육 기관: Martha T T

2019년 11월 28일

I enjoyed going through the course especially the lab sessions

교육 기관: Ujwal M P

2018년 10월 4일

It was awesome to know the first step towards machine learning

교육 기관: Yusuf T T

2018년 8월 27일

I really liked the course how ML is explained and exemplified.

교육 기관: Yang J H

2018년 5월 22일

Good way to start especially coming from the first timer at ML

교육 기관: ADARSH T N

2019년 8월 10일

Learned a lot to dive deep into the world of machine learning

교육 기관: Richard K

2019년 1월 26일

Very good coverage of applying ML to solve business problems.

교육 기관: Sergio R

2020년 8월 18일

Excellent course, the teacher very good, very recommendable.

교육 기관: Muralidhar N

2020년 5월 29일

A very good Introduction to ML and Google cloud capabilities

교육 기관: sheikzaidh

2019년 6월 25일

good explanation for the topics and good practical knowledge

교육 기관: P A

2018년 9월 29일

I learn a lot but i need materials for my future reference..

교육 기관: Meynardo J

2018년 7월 26일

Great intro to the GCP and Google's Machine Learning stack.

교육 기관: Xosue R

2018년 6월 26일

Very usefull, and help to introduce to the machine learning

교육 기관: Jun W

2018년 5월 17일

This course is very inspiring. Thank you Lak and your team.

교육 기관: D.A.S.N. S

2020년 5월 24일

a very good course for beginners to get to know about GCP

교육 기관: Thanh N N

2019년 6월 27일

Great course for beginner, for initial glance into GCP ML.

교육 기관: Arif N

2018년 12월 1일

This course was amazing. I have learnt a lot of new things

교육 기관: Ganesh G

2018년 7월 21일

Very good course. It gave me insights of machine learning.

교육 기관: Sathindu K

2019년 5월 11일

Great course to learn Google ML practices and GCP for ML.