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Voltar para Structuring Machine Learning Projects

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

4.8
stars
34,717 classificações
3,626 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.

WG

Mar 19, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

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301 — 325 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por 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

por 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.

por 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.

por 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.

por 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!

por Muhammad S K

Aug 01, 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.

por 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.

por Aaron B

Nov 01, 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.

por 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.

por 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.

por Jess T

Nov 09, 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.

por amin n s

Jul 14, 2019

This course is unique in content and you cant find anything like it anywhere else.

The amount of experience that Andrew conveys is enormous and practical tips that only can come from a real professional like Andrew.

por Keetha N V

Oct 11, 2019

The course by prof.Andrew Ng gives us a great insight on error analysis and strategies to apply when building a machine learning project to achieve or surpass human level performance in applied deep learning tasks.

por Onkar N M

Aug 09, 2018

I have learnt lots of things on how to structure my machine learning project. I hope that the course wold indeed be very helpful for me in future in my endeavors into fields that are using DL as core technologies.

por Liutov A

Jun 26, 2018

Thank you very much, Andrew Ng. Your course is very cool. It helps to understand better how to handle different tough things and learn very fast. I recommend this course for learning and getting into Deep Learning.

por Mohammad H R

Nov 14, 2019

I think it is a really nice qualitative course which really broadens your perspective about various dimensions of a NN project. It is very eye-opening and very conceptual and honestly, very practical. Thanks Andew

por Shubham G

Nov 03, 2018

thank you for this course, your efforts help me achieve my goal of understanding machine learning and how to apply it to real world and ways of teaching is constantly building my interest in this field. thank-you

por Sinan G

May 12, 2018

Valuable insights into how to structure ai projects with the respect to data, new data, buggy data, synthesized data, mismatched data, and much more such as error analysis and how to use pretrained neural network.

por Pablo T

Feb 14, 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 Seungjin B

Aug 23, 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

Jul 01, 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

Apr 28, 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

Oct 08, 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 M

Aug 26, 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 James M

Feb 07, 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.