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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
estrelas
45,678 classificações
5,209 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

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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4351 — 4375 de 5,152 Avaliações para o Structuring Machine Learning Projects

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.

por aditya g

21 de Fev de 2018

Machine Learning Simulator & course contents well prepares you to how a machine learning project should be structured and approached

por Huang C H

24 de Nov de 2017

Probably the least exciting of the five. This is a short course on how to approach machine learning projects, as the title suggests.

por Priyanka T

22 de Out de 2017

I thought this course was great content wise, but needs to improve on the errata in the content (repeated video sections), and quiz.

por Bingnan L

1 de Fev de 2018

I think it should be useful but since I haven't got many practical experience, the course seems a little bit hard to catch up with.

por Zheng Z

25 de Abr de 2019

I think a little bit more programming homework can help me better understand the concepts, but other than that everything is good.

por Giovanni C

13 de Fev de 2019

It's a good course to gain an initial understanding on the role that different real-world considerations play in Deep Learning NN.