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

4.8
stars
45,248 ratings
5,150 reviews

About the Course

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Top reviews

AM
Nov 22, 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

TG
Dec 1, 2020

I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

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4576 - 4600 of 5,094 Reviews for Structuring Machine Learning Projects

By Pranav B

Jan 30, 2020

Good Course for Beginners need more programming assignments

By Gil E B

Jul 29, 2019

Good Course to learn production pipelines for practical use

By Fereydoon V

Feb 2, 2018

Hope we had programming assignment for this course as well!

By Venkatesh N

Jan 3, 2018

Very good course, It should be last course in specilization

By Richard M

Oct 14, 2020

Interesting ideas, but not as good structured as course 1.

By Pakin S

Nov 28, 2019

Thanks I learn a lot of real world application and problem

By Peter K

Mar 23, 2019

강의 후반부 (2주차) 에 강의 속도가 인위적으로 조정된거 같습니다. 속도가 빨라 이질감이 느껴졌습니다.

By Akshat A

Feb 23, 2019

Curated content, quite exclusive indeed. Respect to Dr. Ng

By Joseph C

Apr 9, 2018

Needs programming exercises to help firm up the new ideas.

By QUINTANA-AMATE, S

Mar 20, 2018

Completely new of what it is out there. Well done Andrew!!

By Alejandro R V

Jan 8, 2018

Not as interesting as the others, I personally prefer math

By Gopala V

Oct 24, 2017

Gave some ideas on mismatched data and how to address them

By Akshita J

Apr 23, 2020

An assignment could have been included to let practically

By Roberto J

Oct 19, 2017

A bit dry, would love to see some more concrete examples.

By Vinicius B F

Oct 22, 2017

Content was fantastic, but the videos were badly edited.

By Suresh P I

Sep 10, 2017

Can be potentially folded into other courses if possible

By Hanqiu D

Jan 9, 2021

It's too easy and cannot be a reasonable single course.

By heykel

Jan 27, 2020

very helpful to build an intuition for DL strategies...

By Rafael G M

Dec 7, 2019

Providing further references would benefit this section

By WEIJIAN K

Nov 15, 2017

You can know well a lot of strategy in machine learning

By B S K

Jul 14, 2020

Good teaching of practical approaches and nice quizzes

By 王毅

Dec 24, 2019

the content is good, but the videos are not well made.

By Shuochen Z

Feb 17, 2019

内容架构很好,讲得也很实用,但觉得课时有些短,许多重要且有趣的问题都未能得到展开详述。期待后续的扩充课程~~

By Gundreddy L M

Sep 11, 2018

excerice should be given for this one proper user case

By Alexey S

Oct 22, 2017

Good class, but 2 previous are much better and useful.