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

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47,494 classificações
5,445 avaliações

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

TG
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.

MG
30 de Mar de 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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4576 — 4600 de 5,407 Avaliações para o Structuring Machine Learning Projects

por Frank H

18 de Nov de 2017

I had some problems answering some questions correctly since there was no specific emphasis in the lectures and I was somehow unsure how to reply.

por Gokhan A

18 de Set de 2017

It has nice discussions on the practical aspects of Deep Learning projects, but I wish it had more Math, and it had more programming assignments.

por Kit B

20 de Out de 2020

Thorough and well taught course on strategy in ML. Would have enjoyed some programming exercises, but the assignments served their purpose well.

por Bradly M

3 de Abr de 2019

This course was relatively short, and the quality of the materials (lecture videos, quiz text) was somewhat poorer than in the previous courses.

por E. M S

30 de Ago de 2017

Good practical advice. I would have added something about agile development and possibly practical advice on NN architectures (depth and size).

por Eloi T

4 de Jul de 2020

Excellent content but the quizzes are badly done, many questions have several reasonable answers and very little feedback if we 'get it wrong'

por Sujay K

25 de Mar de 2018

The course would have been more interesting if we had some programming assignments. Hands on experience into some of these cases really help.

por Daniel M

14 de Jan de 2018

Unique course in the sense that teaches important topics that are rarely seen in the literature and are fundamental in designing AI projects.

por Hagay G

9 de Abr de 2019

Had some pretty great info for junior Project Managers, for some reason, it's also hiding some extremely important info about end-to-end DL.

por Mohamed M H M A

22 de Abr de 2018

Some of the videos weren't of good quality. Also, I was expecting doing a real project not to make decisions based on different scenarios.

por Nikolai K

3 de Out de 2017

Good course overall, would have liked to have the in-depth programming assignments though, those really made the other courses stand out.

por Shashank S S

8 de Jul de 2019

Learned various ways to structure ML projects in industry.

It would have been great to have few programming assignments included as well.

por Leonid M

5 de Out de 2017

Some tips are very useful for practitioners but the same information is repeated over and over again that makes the course quite boring.

por aman a c

18 de Mai de 2020

A small course with very effective tips and tricks to figure out how to start and proceed further while building a project effectively.

por 김진수

25 de Fev de 2019

I think this lecture is very useful when we make our own ML system.

Also, it has many examples about errors we can usually meet in real.

por Tim S

25 de Fev de 2018

Useful, practical material. I probably underappreciate the importance of someone (especially of Dr. Ng's stature) covering this for us.

por Bill T

24 de Fev de 2018

Very practical lessons in this module that should make you and your team more efficient in implementing deep learning on real problems.

por Edward M

24 de Dez de 2019

another great Andrew Ng course. This one gives practical insights in how to go about making your deep neural networks perform better.

por Mohammad H

17 de Dez de 2019

I really found the pilot training quizzes are great and very helpful, but some questions one can debate if has the right answer or not

por Riley

8 de Abr de 2019

Quizzes could be refined since some of the questions are really confusing & need weird pre-requisite knowledge about human physiology.

por Ioannis K

14 de Ago de 2018

It was an interesting course for sure, but it was a bit stretched and the notions explained could be compressed in a much shorter one.

por John E M

31 de Mar de 2018

I appreciate the review and hints on structuring ML projects. Just seemed a little lacking on the meat and potatoes of real practice.

por Saurabh D

26 de Ago de 2020

Now I know what is Machine learning and its parts eg deep learning. The curse cleared the basic structure for machine learning to me.

por JEREMY S

7 de Jun de 2020

Interesting to understand how to manage a problem during a ML project, really good trick and tip! Thanks Andrew and deep learning.ai!

por Alhasan A

1 de Jun de 2019

It would be more useful to give explanation why an answer is correct and others are wrong, such details enhance our learning so much.