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

48,871 classificações

Sobre o curso

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....

Melhores avaliações


22 de nov de 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.


1 de dez de 2020

I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

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526 — 550 de 5,575 Avaliações para o Structuring Machine Learning Projects

por Pablo T

13 de fev de 2018

Teaches how to debug a lot of design and implementation issues that happen when going from theory to practice. This is is the kind of knowledge that you can get from Prof. Ng's experience, but not in a text book.

por Sampath T

27 de set de 2021

I would like to thank coursera to giving me opportunity to follow Structuring Machine Learning Projects course. In the last few weeks I learned a lot of new theories and basics of improving deep neural networks.

por Bibek B

31 de ago de 2020

In this section I learnt about the theoritical part of ML strategy, how to set goal, compare with human-level performance, Error analysis etc which I think will help me to develop as Machine Learning Specialist.

por Seungjin B

23 de ago de 2018

This is a great course but I think it'd be even better to place it after Convolutional NN course. And also wish that there were coding assignments, too, as in other courses in this specialization (Deep leaning).

por Kate S

1 de jul de 2018

This class will give you some practical tips on moving deep learning projects along. How to focus your attention on the most important things to improve. Some techniques for using other work to move yours along.

por Nektarios K

28 de abr de 2018

Great course to understand how best to structure and evaluate the performance of your deep learning project. Invaluable information! I actually used info in this course on my real-world project to great success.

por Jose-Fernando E

8 de out de 2017

Very good course, focusing less on coding / tech aspects and more on the know-how and "art" of the seasoned practicioner. Very useful for acquiring both loose hints and structured approaches. Highly recommended.

por Kapil

26 de ago de 2017

Very useful and practical knowledge. Indeed, this will not be available in any books or theoretical literature. This is very valuable set of suggestions coming from years of experience and research by Andrew Ng.

por Timothy Q

17 de jun de 2020

As Andrew said, you will not find a lot of content in this course in a very structured way throughout the internet or other courses out there. This is a must take if you are a Data Scientist or an aspiring one.

por Terence T

1 de nov de 2020

Excellent course. I really enjoyed being confronted with real life deep learning problems and hoe to go about structuring the project. The "flight simulators" were really beneficial for my learning experience.

por Sean D

9 de set de 2020

Great course with insight into how to prepare your ML and DL projects and the order of operations and caveats and considerations to take into account with your data in real-world scenarios. Highly enjoyed it!

por Christopher M

26 de mai de 2020

Excellent, very valuable to have advice on how to troubleshoot and make progress with a project. ML is not just about equations and code, and this distilled wisdom will help me get started as an ML researcher.

por James M

7 de fev de 2018

This course offers great insights on building a ML project, which are also applicable in different types of projects in real world. Also, this is truly distinguish from other deep-learning courses on internet.

por mitra_00

19 de jan de 2020

Learned about how we should manage our DL project and what to priotize first, these are something one learns after he has gone through such problem, so it was nice to learn about it beforehand from the expert

por Andrew B

7 de ago de 2018

I thought this course was very helpful in analyzing neural networks. While I did enjoy the quizzes, I wish there were more to test my knowledge on whether it is more quizzes or actual programming assignments.

por Minh P

16 de ago de 2017

Very practical, simple short course!

Very good materials that can generalise how to build a good ML model.

Very handful exercise

Nice interview from experts

This is a MUST TRY course, because it's too BEAUTIFUL!

por Username U

29 de jul de 2021

This course was great! This course details various strategies behind creating a machine learning project, as well as the theory behind those strategies. This course is a great mix of practicality and theory!

por Upesh N

19 de mai de 2021

The most informative course that i have ever encountered in this field. I am training deep learning algorithm for my thesis, after taking this course I am able to do a lot of things that improved my network.

por Sergio A D C A

20 de abr de 2021

It was very useful for me to learn about posible sources of error when deploying a machine learning model, and how to fix them as well as improve it with artificial synthesis or transfer learning techniques.

por Marn Y T

27 de out de 2019

As a college graduate who took ML classes in college, this course is a lot more useful in terms of developing an intuition toward iterating on ML projects. The interview with Karpathy is the cherry on top :)

por Yash B

2 de mai de 2020

This was truly amazing! I mean an entire course on the subtleties of gaining skills that we can actually apply in real life is really needed. I am super glad I took this course! Special Thanks to Andrew Ng!

por Marco A

4 de out de 2018

This is a quite different class. It's less math, less formulas but there is so much to learn from the experience of Professor Ng, a whole lot of best practices to follow and tricks to learn. Great contents!

por Dawid D

9 de ago de 2018

Great and unique course! I think that such topics should be a part of any professional ML course.

Having said that, it would be appreciated if the sound volume had higher expected value and lower variance :)

por LZANE-李泽帆

22 de out de 2017

This course gives me an overview sight of the whole process of machine learning project. Not only I know about the technical things, but also know how to structure and point out the position of the project.

por Martin J

17 de ago de 2017

A lot of good thoughts on working with models. I think just getting your hands dirty with some models would help as well. :-) Would be interesting to set up a model to do some difficult tuning exercises.