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

4.8
stars
47,359 ratings
5,436 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

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.

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!).

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4851 - 4875 of 5,397 Reviews for Structuring Machine Learning Projects

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 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 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