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

4.8
stars
45,329 ratings
5,162 reviews

About the Course

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....

Top reviews

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!).

AM
Nov 22, 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.

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451 - 475 of 5,107 Reviews for Structuring Machine Learning Projects

By Asad A

Sep 2, 2019

Really good insights into the practical aspects of structuring projects. Large scale deep learning/ ML is as much about people management and strategic prioritization as it is about complex algorithms and big data handling

By 邱依强

Mar 10, 2018

This is a very useful course since that you can get an impotant instruction to build your own project. You can reduce your time cost and iterate quickly to produce more value by using the knowladges taught by this course.

By arulvenugopal

Jan 8, 2018

Good. However, understanding the importance of strategy, either additional scenario quiz (the simulation type quiz is good) or a programming assignment would reinforce the understanding (given short duration of the course)

By Henderika V B

May 17, 2020

I loved the translation of all the different succesfactors to the daily practice and examples in the course. It gave me an general idea of what to look out for when identifying my own AI problems and defining a NN for it.

By Abhishek R

Sep 15, 2019

This was probably the most useful course of the entire specialization with real-world examples, tips, tricks and techniques on how to approach the problems in Machine Learning world as a whole and Deep Learning in general

By Francisco R

Sep 28, 2017

Even though it's a short course and it doesn't have programming assignments, which I love doing, it has though these case study, which are quite fun and educative, helping you to get started in a Machine Learning project.

By Andrés S

May 24, 2020

I liked this course because I gave me an idea of real situations I could face working on Machine Learning, but I think a little code would've been helpful, for example, to better understand how to do a transfer knowledge

By Ladislav Š

Oct 20, 2019

This part of Deep learning specialization is similar to Machine Learning Yearning written by prof. Andrew Ng. I read the whole book and for me this was mostly a repetitive information - however, very useful and relevant.

By Shishir

Nov 23, 2020

a lot of value for the minimal time invested, and the case study approach was the main reason I would give it 5 stars. Some parts in the videos could be fleshed out more with more real world examples where it was vauge.

By Naresh K P

Jul 25, 2020

This course helped me understand how to prioritize problems that we encounter in Machine Learning space. On the surface this might look simple, but I think this course will have a huge impact as I implement ML problems.

By TANVEER M

Aug 18, 2019

The course taught me about errors how to minimise the errors .How we can improve model performance.satisficing and optimising metrics.Overall the course was quite good.The case studies I found more interesting to solve.

By Akshat A

May 16, 2020

Amazing Course! I generally don't feel like I gain much from lectures and would prefer reading but I'm really glad I took this course, gave me lots of insights into how one would go about improving performance quickly.

By Madalena R

Nov 20, 2019

I really enjoyed this course, I think Andrew has a lot of knowledge on the subject matter and he is able to explain it in a very detailed and understandable manner. The interviews were a plus and also very interesting!

By Bedirhan Ç

Jul 24, 2020

Videos were really help me understand the decision making and strategies for machine learning projects and quizzes were quite good real life simulations of what decisions i could make. I learnt a lor from this course.

By Utsav A

Apr 24, 2020

This case was useful for getting an experienced way of approaching the real-world problems of ML. The quizzes further added to the application of the basics learnt throughout the course. Overall, it was a good course!

By 谢宁翔

Apr 8, 2020

very much wonderful. especially the simulation process, which extracts the pure logic decision process during implementing DNN without actually experiencing all the detailed procedures which are not really challenging

By Lewis C

Jan 27, 2020

Good course. Very interesting!

Having done the course, most of the ideas seem fairly obvious. However, the chances of me coming up with them on my own are almost 0.

Therefore I think the training has been successful.

By Muhammad S K

Aug 1, 2019

It was an amazing experience and I learn a lot of new Machine Learning strategies and error analysis techniques that will help me a lot in my future research work. Thanks a lot, Mr. Andrew, you are an awesome speaker.

By Luiz A N J

Dec 28, 2018

Excellent course, give great practical advice of how to structure projects and to make decisions to improve you models. Those insights are hard to find elsewhere and it's the most valuable contribution of this course.

By Guillermo A M G

Oct 29, 2020

I found very useful this course. It is different of what you'll find anywhere because of its focusing in the strategies for developing deep learning projects. Andrew share his experience in a short but unique course.

By Md. S R

Jul 21, 2020

I really loved the learning of different ways of error analysis and solving issues based on the outcomes of the analysis. This is really a ready to use knowledge for me to implement in my job life. Thank you so much!

By Aaron B

Oct 31, 2018

I would give 4 and 1/2 star because I don't understand some of the questions I missed. I will ask in the forums for more detailed explanation. This is a nice course for a simpler break in the middle of the AI course.

By Joseph F

May 27, 2018

Very nice to get the advices from NG. Wu, But I think it's better to learn this lesson in the last stage when you have a basic understanding of DL and the strategy should be useful when you debug with your DL model.

By Francis C W I

Nov 16, 2017

Excellent. This class gives an overall perspective on how to approach ML projects to ensure that efforts are focused in the right areas to solve problems where the solutions will have the most impact on performance.

By Jess T

Nov 9, 2017

Dr. Ng set the bar very high in the previous two courses of the specialization. This course is also excellent with very useful practical advice, but maybe a little less polished and streamlined than the previous two.