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Voltar para Structuring Machine Learning Projects

Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição

48,866 classificações

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


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.


1 de jul de 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!).

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676 — 700 de 5,571 Avaliações para o Structuring Machine Learning Projects

por Shankar P

4 de jan de 2019

This course is excellent for its content. A few of the quiz questions are difficult to parse, which I have also seen in the other courses I have done on deep learning by Prof Ng et al.

por Srikanth R

2 de mar de 2018

Loved the flight simulator styled quizzes.. learnt a lot on how we can take a systematic approach towards building a right model and how to deal with challenges with data availability.

por Alexei M

16 de ago de 2017

It is probably the best course out of first 3. The approach to week's tests really forces you to think hard. It does look like a very good way to transfer the experience! Thanks a lot.

por Bryan K

31 de jan de 2021

I appreciated the high level guidance that this course offered. It is so easy for me to get bogged down the the details of a technical project and lose sight of the overarching goals.

por Abhinav P S

2 de jul de 2020

The course was nice, and though I initially felt it a bit over-extended with just examples, I find that it helps to gain a deeper insight into structuring the machine learning models.

por Jaffer K

20 de jan de 2020

Interesting learning different metrics which can be used to identify problems in Machine Learning Projects in order to avoid wasting large amounts of time and energy on wrong metrics.

por Anand K M

13 de fev de 2018

A very useful and intuitive course for understanding how to improve a model for different projects and situations. Once again, many thanks to Prof. Andrew Ng for building this course.

por Prashanth S

28 de dez de 2017

Found this course very relevant to me as a newbie. I think following the guidelines mentioned in the course will avoid lot of common mistakes made by many freshers in the field of DL.

por Oleh.Davydiuk

21 de nov de 2017

Professor Andrew Ng explains very clearfull in detail about challenges regarding deep learning products development and how to face them using systematic approach. Strongly recommend!


17 de out de 2017

This is exactly why I took this course: to hear about things that you do not read very often, about machine learning practical problems and how you can solve them. Really interesting!

por akshay b

29 de set de 2017

A very practical and unique course exploring various real life aspects of machine learning applications.A must for someone who aspires to solve real life problems using ML algorithms.

por Christian B

24 de set de 2017

This course gave a nice overview on systematically tackling machine learning tasks and problems. The "flight simulator" quizzes were very helpful in understanding the course material.

por Omer M

14 de nov de 2020

This course is nicely structured, and contained many important information

The teacher delivered the course in a very simple yet highly informative and understandable way

Many thanks

por 박영현

16 de mar de 2020

Highly helpful course. The videos of this course improve the insight of machine learning / deep learning tasks. I will refer to the theories that I learned in this course every time.

por Lois A L

21 de jan de 2020

This is phenomenal. I was working as an undergraduate student researcher in two different projects right now and what was discussed here really gave me the eyes that I really needed.

por hiten s

3 de out de 2019

this course helps me how to create a plane of the machine learning project for my team and also individual project like the use of transfer learning and multi-classification problem.

por Nicholas Y

20 de jun de 2019

Great way to understand step by step all important aspects of creating a machine learning project. Finding out what problems can be faced while creating a model and ways to fix them.

por Brian B

22 de out de 2017

This course was filled with practical advice to quickly build, iterate on, and improve ML models. It's more directly relevant to real-world ML work than any other course I've taken.

por Roxana N V

8 de out de 2017

Best ever course in deep learning. By this far, you should have strong foundations about working deep learning, and this course helps you to master the ML strategy for your projects.

por Muskan G

23 de dez de 2019

Short and crisp course. It was very informative to learn how to do error analysis on practical machine learning projects. I also really enjoyed the unique assignments in the course.

por abhishek h

4 de jun de 2019

Great course. All errors explained nicely.Covered mismatched data distribution very well. Also transfer learning, multiple task learning were explained nicely. Overall great course.

por Manuel A

5 de mai de 2019

Review of techniques and strategies. Very interesting. As there is no programming assingment, I would advice to add some Keras-TF lessons to be ready to tackle the following courses

por Ka W P N

9 de mar de 2019

Well structured course. Worth spending the time watching all the videos to get a full picture of what are the key things that really matter when planning and launching the projects.

por Line C

10 de jul de 2018

I loved the idea with the case studies to flight simulators. This is a very useful way to practice working with machine learning problems in short time and in a classroom situation.