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Machine Learning Pipelines with Azure ML Studio(으)로 돌아가기

Coursera Project Network의 Machine Learning Pipelines with Azure ML Studio 학습자 리뷰 및 피드백

4.6
별점
594개의 평가
99개의 리뷰

강좌 소개

In this project-based course, you are going to build an end-to-end machine learning pipeline in Azure ML Studio, all without writing a single line of code! This course uses the Adult Income Census data set to train a model to predict an individual's income. It predicts whether an individual's annual income is greater than or less than $50,000. The estimator used in this project is a Two-Class Boosted Decision Tree classifier. Some of the features used to train the model are age, education, occupation, etc. Once you have scored and evaluated the model on the test data, you will deploy the trained model as an Azure Machine Learning web service. In just under an hour, you will be able to send new data to the web service API and receive the resulting predictions. This is the second course in this series on building machine learning applications using Azure Machine Learning Studio. I highly encourage you to take the first course before proceeding. It has instructions on how to set up your Azure ML account with $200 worth of free credit to get started with running your experiments! This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰

MT

2021년 8월 15일

It was an excellent learning from a novice like me in the last part of the project I got lagged but the rest I learned thank you i hope i can attend more projects like this to gain more experience

AT

2020년 6월 5일

I have learn most quality things and practical knowledge with machine learning pipelines with Azure ML studio which is very useful for our future & It can help me in my life.

필터링 기준:

Machine Learning Pipelines with Azure ML Studio의 97개 리뷰 중 51~75

교육 기관: md m

2020년 9월 16일

Very Good

교육 기관: Er. A B S

2020년 9월 12일

Excellent

교육 기관: Kamlesh C

2020년 7월 23일

Thank you

교육 기관: MIGUEL A C L

2020년 10월 12일

EXELENTE

교육 기관: Amusan E

2020년 9월 18일

Splendid

교육 기관: Hewavitharanage S A G

2021년 6월 12일

awesome

교육 기관: John P G A

2020년 9월 16일

Nothing

교육 기관: 191PH021 L G

2022년 5월 18일

LUFSeu

교육 기관: Jagadish B

2020년 9월 16일

Thanks

교육 기관: Mohammed R I

2021년 1월 3일

great

교육 기관: Richa S

2020년 9월 16일

Great

교육 기관: RAKSHITH P

2022년 2월 11일

GOOD

교육 기관: SONALI H

2021년 10월 30일

nice

교육 기관: Vamsi k C

2020년 9월 20일

Good

교육 기관: Sk I A

2020년 9월 16일

Good

교육 기관: GURUDAS B

2020년 9월 16일

Nice

교육 기관: ABDUL J C

2020년 9월 13일

good

교육 기관: Rajula n

2020년 9월 11일

Good

교육 기관: p s

2020년 6월 26일

Good

교육 기관: tale p

2020년 6월 13일

good

교육 기관: Battu u

2020년 5월 18일

Nice

교육 기관: Qusaya

2021년 6월 17일

w​u

교육 기관: Manjunath G

2021년 8월 19일

to

교육 기관: bejadi u

2020년 6월 21일

5

교육 기관: James J H O

2020년 12월 19일

This specific project does not include any programming (of which I wanted) but it does provide a practical overview of how machine learning methods can be implemented through using Azure. The project is relatively short so could be completed very quickly of which was a plus for me. The instructor explains concepts and ideas well all throughout the course and I would recommend this course to anyone who wants a flavor of how machine learning can be implemented.