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

4.8
stars
49,877 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

ED

Aug 22, 2020

Excellent start for digging into topics that are not taught nowhere else. The author books 'Machine Learning Yearning' is a great next read that goes deeper in some of the aspects, really recommended.

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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1051 - 1075 of 5,718 Reviews for Structuring Machine Learning Projects

By David R N

Sep 21, 2021

Excellent course, where you learn to diagnose a model and prioritize possible improvements in a machine learning project. Highly recommended.

By Kiet P

Jun 28, 2020

So far I feel like this is the most important course in this specialization. Please focus because it will save you a lot of time in the future.

By Vibhutesh K S

Oct 3, 2019

Well its a very straight forward course. Very easy, not very technical but a general overview of What to be done in a Machine learning project.

By Aron F

Aug 28, 2019

Really great course, in difference with the first 2 courses this has got a lot of concepts, but those are clear and kind of easy to understand.

By Juan P U C

Apr 17, 2019

I rarely rate online courses. However, this was completely worth it! Excellent course with a lot of "know-how" knowledge. I fully recommend it.

By Sergei S

Mar 31, 2019

Among other courses of this series, this course brings up some of the most important things every (deep learning) scientist should be aware of.

By S L

Mar 24, 2019

Andrew Ng is such a great teacher, it is a pleasure to learn machine learning and deep learning from his well thought-out lectures and examples

By HAMID S

Oct 23, 2018

Awesome . Thank you Andrew N G for these very valuable beautiful concept boosting insights .Very Very good . Really awesome insights and quizes

By Manjunath M

Jul 8, 2018

Great Course, learnt many new aspects that are found nowhere on Internet or Books.Thanks Stanford, Thanks Prof Andrew and Assistant Professors!

By Fares I

Jun 30, 2018

I enjoyed the course, the information provided were very beneficial and its not something you can easily read about in other courses or online!

By Pierre F

Jun 24, 2018

Excellent training to get organized in a Deep Learning project, explaining on real use cases how to select the multiple approaches and tactics.

By Fady B

May 24, 2018

a very important course providing real life experience with problems we face in our projects. it's a much needed skill that everyone must have.

By Albert M

Mar 6, 2018

This is the kind of advice you wish you have had in your last ML / DL project. I really appreciate all the information given by the instructor.

By Navy X

Oct 1, 2017

This course expands my view on ML, for example how to analyze errors, and how to make a decision that leads an AI project to a right direction.

By Florian C

Jan 16, 2021

Really helpful course for getting a better idea of how to approach a deep learning project and what steps to take during the development phase

By Kathiresan S

Aug 16, 2020

Great course, loved the content! The instructor provided great advice on how to tackle problems one might encounter while training neural nets

By 김홍숙

Aug 9, 2020

Plenty of pratical experienece and guidelines that can be used in the practice of DL network defintion and planning of workflow related to DL.

By Sandeep P

May 21, 2020

Nice explanation of how to work on deep learning project. Course explains practical aspects, which otherwise I would never understand. Thanks,

By Sreenivas M

Jan 30, 2020

Really well structured concise course. Knowing what to do when in a machine learning project is really important and this course teaches that.

By Armaan B

Aug 17, 2019

Wish I'd done this coarse 2 years ago when we started working on our own ML problems. It's extremely insightful. Will certainly revisit again.

By Sumandeep B

Dec 17, 2017

Very good intuitive insights into designing the best suited DL solution as well as making the most out of data and improve system performance.

By Jingbo L

Nov 20, 2017

It is very helpful to have a big picture of where the project goes, and how to make a good use of time to make a bigger impact on the project.

By Cameron D K

Nov 18, 2017

The material in this course is very important. It is not found in books or easily found on the Internet. Very valuable and highly recommended.

By Adarsh

Nov 9, 2020

Really great course for getting to know thee errors in deep learning and how to deal with them. Good explaination of Train , dev , test sets.

By Tarun S

May 23, 2020

A well organized and structured course for anyone who wants to optimize the performance of their model and do the error analysis efficiently.