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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

4.8
stars
50,118 ratings

About the Course

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng鈥檚 experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

MG

Mar 31, 2020

It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.

YP

Jul 26, 2018

Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN鞚� 鞁れ牅 鞝侅毄頃犽晫 氚橂摐鞁� 鞚错暣頃橁碃 鞝侅毄頃挫暭 頃� 鞁れ鞝� 雮挫毄霌る 甑劚霅� 氅嬱 旖旍姢 鞛呺媹雼�!

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5201 - 5225 of 5,745 Reviews for Structuring Machine Learning Projects

By Carlisle

鈥�

Aug 21, 2017

Introduced a lot on engineering project experiences

By Marcelo A H

鈥�

May 29, 2020

Very interesting topics were shown in this course.

By William L

鈥�

Apr 18, 2020

Very useful knowledge that is not commonly taught.

By Alvaro G d P

鈥�

Nov 28, 2017

Interesting but perhaps we could have gone deeper.

By John H

鈥�

Aug 27, 2017

Is the flight simulator hw going to be added soon?

By Pat B

鈥�

Dec 9, 2019

Great course. I liked the compact, 2-week format.

By liu c

鈥�

Mar 17, 2018

A little bit abstract. But still very inspiring!

By Florian M

鈥�

Aug 25, 2017

Very interesting tools and ideas for applied ML.

By Nicholas N S

鈥�

Apr 28, 2021

There is so much noise in the explanation voice

By Jason G

鈥�

Nov 25, 2018

Not as strong as the other 4 of 5 of the series

By Mark

鈥�

Oct 13, 2018

Great course. Needs deeper practical examples.

By Francis J

鈥�

Feb 26, 2018

A lot of insights rather than technical details

By Luk谩拧 L

鈥�

Jan 7, 2018

Coding exercises would be great in this course.

By Mares B

鈥�

Nov 17, 2020

A little short, maybe more hands on exercises?

By Ed G

鈥�

Nov 9, 2020

Concise course with some interesting concepts.

By Tulip T

鈥�

Jul 23, 2019

Quite helpful when you start a new ML project.

By S V R

鈥�

Nov 5, 2018

The session were simple, could be more complex

By Caique D S C

鈥�

Jul 31, 2018

very good course, could be less massive though

By Ivan V

鈥�

Dec 11, 2019

I want a program exercise like in 1-2 courses

By Dionysios S

鈥�

Nov 30, 2018

I would like to see more practice assessments

By Luis E R

鈥�

Aug 1, 2019

Very useful concepts that few people address

By Jun P

鈥�

Apr 23, 2018

Kind of boring than the cnn and rnn class ..

By John H

鈥�

Aug 29, 2017

Useful content, could be much more succinct.

By vijaykumar

鈥�

May 15, 2020

This course is awesome and good knowledge .

By Alfredo M

鈥�

Mar 14, 2018

There were no practical coding homeworks :(