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

4.8
stars
44,142 ratings
4,976 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

JB

Jul 02, 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!).

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.

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4451 - 4475 of 4,923 Reviews for Structuring Machine Learning Projects

By Pablo L

Oct 30, 2017

Great set of guidelines. Mostly theoretical, though.

By Cristina G F

Oct 22, 2017

Concrete reminders of important and practical points

By Ktawut T

Oct 10, 2017

Very useful materials for leading a ML research team

By awalin s

Sep 29, 2017

interesting insights about real world implementation

By Yu L

Apr 03, 2020

would like to have more excercise related to coding

By Mage K

Mar 07, 2018

Would've liked to have some programming assignments

By Carlisle

Aug 20, 2017

Introduced a lot on engineering project experiences

By Marcelo A H

May 29, 2020

Very interesting topics were shown in this course.

By William L

Apr 17, 2020

Very useful knowledge that is not commonly taught.

By Alvaro G d P

Nov 27, 2017

Interesting but perhaps we could have gone deeper.

By John H

Aug 26, 2017

Is the flight simulator hw going to be added soon?

By Pat B

Dec 08, 2019

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

By liu c

Mar 17, 2018

A little bit abstract. But still very inspiring!

By Florian M

Aug 24, 2017

Very interesting tools and ideas for applied ML.

By Jason G

Nov 25, 2018

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

By Mark

Oct 13, 2018

Great course. Needs deeper practical examples.

By Francis J

Feb 25, 2018

A lot of insights rather than technical details

By Lukáš L

Jan 07, 2018

Coding exercises would be great in this course.

By Tulip T

Jul 23, 2019

Quite helpful when you start a new ML project.

By S V R

Nov 05, 2018

The session were simple, could be more complex

By Caique D S C

Jul 31, 2018

very good course, could be less massive though

By Ivan V

Dec 11, 2019

I want a program exercise like in 1-2 courses

By Dionysios S

Nov 30, 2018

I would like to see more practice assessments

By Luis E R

Jul 31, 2019

Very useful concepts that few people address

By Jun P

Apr 22, 2018

Kind of boring than the cnn and rnn class ..