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

4.8
stars
46,151 ratings
5,271 reviews

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

JB
Jul 1, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

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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4676 - 4700 of 5,215 Reviews for Structuring Machine Learning Projects

By Daniel A L G

Sep 21, 2020

The course is so useful, but sometimes the voice turns so low

By Paweł P

Oct 11, 2019

Good overview of the problems occuring while training models.

By Sathiraju E

May 25, 2019

Thank you, Andrew.

This course was very helpful though theory.

By Daniel Z

Aug 14, 2018

Good course. It would be better with programming assignments.

By Antonio H

Jul 2, 2018

I could not do the flight simulator test, it was not working.

By Youjiang Y

Jan 16, 2018

It will be really nice if there is assignment for this course

By Dioselin E B P

Jan 13, 2021

It's much information for only a one questionnaire for week!

By zhang l

Mar 16, 2020

Some of the questions in the quiz set seems a bit confusing.

By gayatri h

Jun 4, 2019

It gives the idea about real life machine learning problems.

By David d V

May 24, 2018

It would have been great to add some programming assignments

By Jeff O

Sep 11, 2017

Good material, just wish it had more "labs" to work through.

By Juan C M S

Jun 8, 2020

In some occasions it's been has a bit redundant information

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