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

4.8
stars
48,334 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

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.

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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426 - 450 of 5,519 Reviews for Structuring Machine Learning Projects

By Long C

Jun 26, 2020

Great and detailed strategies especially for people working on a machine learning projects. With good strategies, time and money may be saved. A really good complimentary material to Andrew's new digital book: Machine Learning Yearning.

By Aditya G

Dec 23, 2019

Highly recommended as it helps one think how to improve their ML models. Just do a 60/40 split and hoping for the best result is not the way to go, and this course definitely helps unveiling how to remove bias and variance from a model.

By Chulhoon J

Oct 15, 2018

this course has very practical and helpful advices to solve problems related to the deep learning algorithms. I believe those valuable advices and tips will be able to reduce tremendous times and efforts when you stuck with the problem.

By Alfred D

Jan 19, 2018

One of the best tips to use in real ML consulting projects; Prof Andrew Ng is an awesome teacher

and keeps you engaged , by giving relevant industry use cases for each topic being taught; This

brings objectivity and motivation to learn.

By Ketan D

Aug 16, 2020

Best course so far in specialization as technical stuff you can google and get tons of books and blogs for . But for real world insight into how to solve problems is a great thing to know and not easy to find out from other resources .

By Marcin S

Feb 20, 2018

If it were possible I would give 6 stars! The most valuable deep learning course I'v ever seen. There many more technical courses but related knowledge can be found in books/on lectures. Knowledge learn from this course is exceptional.

By Hisham R

Dec 20, 2019

Actually, the information in this course were very valuable since they could be only gained after long time of real practical experience. Transfer learning, multitask learning and error analysis topics are priceless. Great course IMO.

By 谢志文

Dec 5, 2017

I think it will be more helpful for those who have actually worked on real ML project,for me, it's still kinda abstract and a little boring except for the week 2 ,so it's worthwhile to learn it again once I get some experience in ML.

By Ihor F

Oct 12, 2017

Course is time-consuming because it with high concentration with information. Would be maximum useful for those who have some experience in machine learning.

I am very excited! Quizzes are so interesting and close to real life project.

By Michael O

Jul 27, 2022

This is a very good course if you want to have a real-life sense when approaching machine learning problems. It is one of those skills that is hard to get in a regular classroom, and takes several mistakes to realise in the industry.

By Brian D

Jul 21, 2021

This course was not what I had thought it would be. It helps to bring back the human dimension into the side of coding. Shines light on the importance of the process, and how decisions will impact the ultimate success of the project.

By mcvean s

Jul 23, 2020

An exceptional course to hone your skills, and develop efficient Machine Learning and Deep Learning systems to better address the problems faced in the real world. The added experiences of Andrew are an asset to the learning journey!

By Abe E

May 9, 2020

Really useful quiz questions. I liked this class a lot even though there were no programming exercises. Getting some insights into the facial recognition and image classification stuff before course 4 was also really nice. Thanks! :)

By Eugene L

Dec 22, 2019

Good course with a lot of qualitative information that is quite useful. Giving it a 4 because it would have been great if there were accompanying Jupyter notebooks. It's a solid course overall and I recommend it to anyone interested.

By Prakhar D

Jul 21, 2019

This course is highly intuitive, practical and less mathematically complicated. Prof Andrew Ng uses many examples to elucidate concepts. Post learning one will be capable of choosing which direction to go in solving an ML/DL problem.

By Kadir K

Oct 20, 2017

This was a great lecture from Andrew Ng. I have learned basics of error analysis, multi-task learning and structuring a machine learning project in general. This will be very useful staff for my professional career. Thank you Andrew!

By Carlos Z C

Jul 16, 2021

I consider this course is a truly gem because of the bunch of good practices every person getting into the field should be aware of. I also liked how quizzes were designed to address industry use cases and not just academic details.

By Virginia A

Apr 7, 2020

Excellent point of view. many teach you how to do /write code to apply ML to your problem. in this course I felt they were teaching me how to understand the results and how to improve it. Extremely interesting for potential Managers

By Hugo T K

Jan 17, 2020

This course is exceptional since we can learn a lot with Andrew Yang's great experience with Machine Learning Projects. It'd also like to suggest to add new classes about powerful and newer techniques, such as feature visualization.

By Prashant T

Dec 18, 2019

These are most toughest things, in which people takes 100 of hours to explain and still people confuse. But by doing this course within a 4 hrs span you will have a decent knowledge. Kudos!! to entire team and thanks a lot AndrewNG

By Antonio C D

Feb 14, 2019

This course covers lots of practical advice and techniques resulting from real world project experience by the author. I highly recommend this course to anyone involved in deep learning projects, even if not in a technical position

By Sai K

Dec 14, 2018

this course very important other than previous courses because we need to understand the data and split the data set across the train, dev and test and making strategies for training the dataset using model. Thanks for this course.

By Justin T

Oct 16, 2018

Great course with some awesome insights into structuring the analysis of machine learning models. Definitely picked up a ton of strategies, tips, and tricks that I will be using as a I move forward with my machine learning career!

By dunyu l

Nov 20, 2017

The mindful advice does not only deepen your understanding in deep learning, but also stimulate creative thinking in my own PhD research in a total different field. It is also enjoyable to watch the interviews, which I favor a lot.

By Sixian C

Mar 12, 2022

very helpful!

Andrew teaches a lot of knowledge that can't find in books.

This kind of knowledge is very helpful for student when he gets his hands on real-world ML project.

Error Analysis & Bias& Variance are all useful techniques!