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

4.8
stars
49,631 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’s 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

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.

MG

Mar 30, 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.

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5126 - 5150 of 5,688 Reviews for Structuring Machine Learning Projects

By Pakin P

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 Ann D

Sep 10, 2023

nice short course. Quizzes were more difficult, though

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 Sreenivas 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.

By Lei C

Sep 25, 2017

the answer of the assignment is a little bit arguable.

By SANJAY P

Oct 6, 2020

Content is good. Presentation could have been better.

By Kumari P

May 28, 2020

machine learning project are highly iterative as you.

By Diego S

Feb 18, 2020

I miss notebooks for practice, besides questionnaires