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Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição deeplearning.ai

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36,102 classificações
3,847 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

AM

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.

MG

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.

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151 — 175 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Kwan T

Oct 01, 2017

I am very lucky to be able to learn from Andrew the DOs and DON'Ts of how to develop a successful practical deep neural network for real applications. It would take a machine learning developer many years of working experience to acquire any one of the topics that Andrew articulated in this course. Thank you so much!!!

por Mark Z

Jun 11, 2019

I've decided to take this course after seeing its feedback from other people and the comment which got me was the following: "This course is could be summarized as a machine learning master giving useful advice". I think it perfectly describes the course's content. This course is definitely worth investing time into.

por Dunitt M

Feb 10, 2019

Excelente curso, muy recomendado para quienes tienen una idea de Deep Learning pero con frecuencia se encuentran en situación que no saben cómo afrontar o cuál camino intentar primero. El conjunto de habilidades impartidas aquí no te harán un mejor programador, pero te ahorraran muchas horas de esfuerzo innecesario.

por Gaurav K

Sep 07, 2017

Amazing tips shared for structuring machine learning projects, which were ignored in most of the other ML books. Building a model is one thing, but tuning it to make it work better in the real world is more important which this course focuses.

Thanks Prof. Andrew Ng for the consistent support of spreading knowledge!

por Yuezhe L

Nov 20, 2018

This is a very helpful class. I have been working on machine learning projects for years. This course provides methods to systematically trouble shoot problems in a machine learning project. Despite all the samples are using neural networks, the methodology can be applied to improve other machine learning projects.

por Bernard O

Oct 25, 2018

Excellent course on managing through the thick of bias/variance tradeoffs. Been doing a lot just based on things I have picked up through experience, but this course puts a the quantitative rigor and discipline behind the art. The sections on transfer and end to end deep learning were eye opening sections for me.

por Gema P

Feb 25, 2018

This course is strategically very important so congrats on making it

I would add a programming assignment including transfer learning or multi-task learning implementation due to the multiple cases of use that are today in the industry.

Thanks again for making this Wonderfull material available to the community ^^

por BAZIL F

Dec 29, 2019

Very useful course for understanding nuances of AI and different useful techniques in strategizing the approaches. Extremely useful in architecting, designing and delivery of the complex solutions involving AI (even as a sub-component). Prof. Andrew Ng is always a pleasure and honor to learn from. Thank You Sir!

por Harvey Q

Sep 04, 2017

Really inspiring course, and UNIQUE. No other class, I think, provide these suggestions on the big question "what's next?" in ML projects. The videos are a bit weirdly sequenced. But they provide very systematic ways of project starting, data splitting, model evaluating, problem finding and tuning. Great course!

por Pedro B M

Feb 28, 2019

This a course on key practices one should have when developing a ML project. Once again Andrew Ng is very pedagogical, teaching sometimes complex concepts in a easy to understand and practical way. I particularly liked the case studies, where the learned concepts had to be put into practice for decision taking.

por Niyas M

Oct 29, 2017

What a great session! Full of practical advice and strategies to help you iterate fast. Prof. Andrew draws on his years of hands-on experience at top companies to put together the best practices for structuring your machine learning projects. This has been the most valuable course in this series for me so far!

por Zebin C

May 18, 2019

In the course, I learned how to divide train set, dev set, and test set, and how to solve the problem of different distributions of train set and test set. Impressive is the transfer learning. Transfer learning is a very effective way to help me provide a completely different approach to solving new problems.

por Swapnil T

Mar 31, 2020

What can be better than this, a highly qualified and passionate individual explaining what he has observed and learnt from the mistakes of other professionals , those who themselves are one of the smartest brains so that we don't make mistakes or waste our time realizing that we were hitting something wrong.

por Vishnu V

Mar 08, 2020

Excellent course to understand the ML project pipeline and then to analyse the various problems that could pop up during an ML project. The tips and tricks that we obtain from this course to address those problems are really valuable and unmatched. It is truly one of its kind course from the master itself!

por Abhilash V

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.

por Fahad S

Sep 06, 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.

por Tushar M

Mar 17, 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.

por Edward D

Oct 12, 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.

por J.-F. R

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.

por 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!!!

por Zoheb A

Feb 05, 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.

por João F

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!

por Lien C

Apr 04, 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!

por 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.

por Jialin Y

Apr 22, 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.