Chevron Left
Voltar para Structuring Machine Learning Projects

Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição

40,655 classificações
4,488 avaliações

Sobre o curso

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....

Melhores avaliações


Nov 23, 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.


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.

Filtrar por:

326 — 350 de 4,453 Avaliações para o Structuring Machine Learning Projects


Oct 28, 2018

Excellent course on understanding how and what to prioritise in ML projects. Not just helpful for people leading ML teams, but also for people who are doing some independent projects. ML is a lot of fun when you do experiments for fun :)

por Mohamed C S

Jul 19, 2018

Excellent Course, though it is an optional course, it is really worth taking it!

The Use case studies are just excellent! You can really have a taste of the problems encountered when you have to manage a deep learning project. Great work!

por Omid M

Jan 21, 2018

Great tips!

Minor issue: often the request for feedback for a lecture came right at the beginning of the lecture, covering big portion of the video ('was this video helpful'! ). It was annoying (I couldn't figure out how to minimize it).

por Long C

Jun 27, 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.

por 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.

por 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.

por 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.

por 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.

por Hisham R

Dec 21, 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.

por 谢志文

Dec 05, 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.

por Fesianov I

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.

por Abe E

May 09, 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! :)

por 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.

por Prakhar D

Jul 22, 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.

por 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!

por Virginia A

Apr 07, 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

por Hugo T M 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.

por 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

por 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

por 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.

por 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!

por 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.

por Satyam D

Jan 06, 2019

Dear Prof Andrew Ng, grateful to you and your team for yet another excellent course in Deep Learning specialization. ML Strategy teaches us important practical aspects which are absolutely essential for the success of ML projects.

por Julien D

Sep 09, 2018

This course give a substancial idea of how to deal with Machine Learning project.

It is only a two week course with 3-4 hours per weekd but is at the same price as the others.

Though it is still an excellent course that I recommend.


Apr 14, 2019

Excellent course that covers some of the most critical aspects related to machine learning projects. The approach used in the quizzes is very effective. It introduces learners to some common problems under a variety of scenarios.