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

4.8
stars
49,627 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.

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.

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251 - 275 of 5,688 Reviews for Structuring Machine Learning Projects

By Abhilash

•

Sep 11, 2017

This is a good course to get a feel of real projects and insights on how to go about executing them.I got some good tips to approach a deeplearning project.I don't know if this is too short of a course but I would trust Andrew Ng if he thinks this is fine to get a sense of deep learning projects.

Thank you.

By Fahad S

•

Sep 6, 2018

The content is very unique and extremely insightful in how to structure a machine learning project. As a machine learning practitioner, I can personally vouch for the usefulness of the suggestions made by Andrew NG. Had I known all of this before, it would have saved me a lot of time on numerous projects.

By Tushar M

•

Mar 16, 2018

This is the best ML course I have taken so far. A lot of ideas around train/dev/test sets, bias variance trade-off and difference of data distributions between train and dev sets snapped into place for me. I am sure it will take me a while to internalize this content but I feel like I have found the path.

By Edward D

•

Oct 11, 2017

Brings a lot of useful insight of how to tune the model more from the data point instead of the model or algorithms. This could be super helpful in solving real world problems. Also the two case study homework helped me a lot to get a better understanding of what Andrew meant in his lecture. Great course.

By Shivam S

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Jul 15, 2020

The thing is to get started, sir Andrew has given huge insights in working of Neural Networks and driven us through the different parts of the journey. This is not just a course but a story that every Deep Learning enthusiast must go through to see the difference. Eye opening Experience.

Thank You

Andrew

By Smail K

•

Jun 3, 2020

Another amazing course on deep learning and machine learning in general! This course gives you amazing insight into how you could strategize while running a machine learning project. I enjoyed going through the content of this course a lot, but not as much as the case studies! they seemed very realistic.

By Hari K

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Oct 22, 2020

Very practical advice for a beginning deep learning engineer on what to do to avoid getting lost in the hyperspace of all the parameters one could change to train a better neural network model. I do wish however there was more explanation of why the different heuristics work, that Prof. Andrew suggests.

By Ashwin K

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Apr 29, 2020

Good practical tips for planning out your machine learning projects. Every machine learning engineer should check out this course as it will be really helpful in planning your machine learning projects and allocating time for tasks in the project. And as usual, great, lucid instruction by Andrew Sir! :)

By Jacob J

•

Jun 19, 2023

A great course for AI practitioners and system designers, like Systems Engineers, Product Managers and Strategy Consultants. What I like most about the Deep Learning specialization courses is the focus on the overall system design considerations without going too much into the mathematical derivations.

By Carlos A L P

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Nov 24, 2020

Very interesting to see a transversal course of how to model and manage ML and DL projects, I am happy to learn new tricks to deal with train/dev/test sets with different distributions, dealing with small datasets and new techniques to apply transfer learning and lastly, how multi-task work in general

By J.-F. R

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Feb 18, 2020

Great course by Prof Ng. I had taken his Machine Learning course a few years ago, so expected high standards of content and assignment preparation - I was not disappointed. Staff is very responsive and helpful in forums as well. I highly recommend it. Taken as part of the DeepLearning specialization.

By Ayush K

•

Jan 19, 2020

Amazing course where Andrew NG shares his advice on how to work with datasets of different distributions etc. Coming from such an experienced practitioner is so helpful.

The Quizes are really helpful as they deal with case study and really make you feel like you're in the spotlight

Loved this course!!!

By Zoheb A

•

Feb 5, 2019

The two quizzes of this course were unique. Never came upon such a quiz in any other online course. Along with the videos and supplementary pdfs, this course was quite unique and important in every aspect. I will use the approach I learnt here on my next ML projects. Thanks to Andrew Ng and the team.

By Arturo R

•

Jul 15, 2020

Really good course. As a machine learning practicioner I discover new ways to attack a machine learning problem. It taught me where should I focus to achive my goals faster. I think that in the exams they could give a little more explanation of why some answer is wrong. Overall an excellent course.

By João F

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May 25, 2019

Very good course. Professor Ng explains very well why some strategies are better than others and how a deep learning practitioner or team can save a huge amount of working hours by following the instructions taught in this course. There are also useful, in-depth discussions in the forum. Thank you!

By Lien C

•

Apr 4, 2019

Great practical insights of how to start a ML project, how to improve/optimize the system, how to identify and troubleshoot common problems in deep learning. The course provides comprehensive high level guidelines for anyone who uses machine learning, even without having any programming experience!

By Dariusz J

•

Jul 19, 2019

The course has practical content. When took in the Deep Learning Specialization I noticed that some parts of the material were already known from previous courses. Indeed, in previuos courses the repeated aspectes are presented from a different angle, but probably there is an area for limiting it.

By Jialin Y

•

Apr 21, 2018

It's like understanding deep learning: a team leader's perspective. Andrew may be the first instructor to give this kind of course. Based on his experience in building practical and large scale machine learning system in Google and Baidu, the course content is highly inspiring and worth listening.

By Ged R

•

Oct 3, 2017

As an Ops person by nature, i like to see methodology and structure along with systematic approaches to results - be they solutions or problem solving. This course adds to that area, by providing best practices and ideas, it forms the basis from which these challenges can be addressed. Very good.

By Akshay M P

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Sep 25, 2020

THE must have course for every machine learning enthusiast!! The course is very enjoyable with invaluable insights and expertise from a well-rounded deep learning practitioner. It greatly helps to clear the machine learning workflow and best practices to quickly develop, iterate and ship a model.

By Mihai L

•

Jan 28, 2018

This course had no programming assignments. Yet I found it amazing. It truly gives you insight into how to engineer your projects to account for real world conditions.

Liked the flight simulator analogy to this course. Accelerated learning is really the great benefit of following Andrew's advice.

By Gabriel L

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Aug 25, 2017

I've done a Master degree in IA and the things covered in this course have never been addressed by any of my professors. Now I've been working in a Machine Learning team for the past two years now, and I believed these lessons would have been of great value, and would have saved me a lot of time!

By Miad M

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Dec 21, 2021

I Thought I knew every thing from what I've learned in previous courses but in this one, I do learned a lot more and even some of questions which didn't strike into my mind and I think they are questions I would be faced in the future, were answered here. thank you for this comprehensive course.

By Ruben G

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Aug 7, 2020

This a great course on Deep Learning, the contents are so full of interesting information, actually, this course could also be called "Everything you wanted to know about Deep Learning (but were afraid to ask)".

As always, Andrew delivers a great course, whose content is ready to put in practice.

By Julio E H E

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Jun 16, 2019

This course is very helpful to learn best-practices and problem-solving strategies that can help improve our deep learning algorithms. While I think the ultimate way of learning is through practice, here you can at least get a list of things to try in the future as you work on these algorithms.