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

4.8
estrelas
47,333 classificações
5,432 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

AM
22 de Nov de 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.

JB
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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4476 — 4500 de 5,393 Avaliações para o Structuring Machine Learning Projects

por Sandeep J

30 de Jan de 2018

Great class. Homeworks don't encourage independent thought. It would be nice if the material would spell out the problems that need to be solved more clearly, before describing the solution.

por liubai01

15 de Set de 2017

That is a good course that teaches you many useful tricks in machine learning. However, some mistakes in quiz make me feel puzzled. In general, it is a good course that you should not miss.

por Rufo S

19 de Set de 2017

Very good course with important topics. The Quiz 2 should be reviewed because has some inconsistencyies has mentioned in the forums. Some more pratical assignment would be also appreciated.

por Michael B

12 de Mar de 2018

I was a little disappointed that this course didn't have any programming exercises. That being said, I really like how the quizzes make you think of a real world application. Great stuff!

por Vassilios V

11 de Fev de 2018

Very good advice that is hard to find anywhere else. The quizes however have some ambiguous cases which are borderline wrong. At least they should be explained better after the completion

por Radu I

23 de Out de 2017

Interesting opinions on what strategy to take to drive ML projects forward. Here and there you must weigh in with some "numbers" that suit you/your team but it's informative, nonetheless.

por Bryan H

29 de Mai de 2018

The course appears to be in development and could be strengthened with programming assignments that take you through an actual mock project. Otherwise, the current content is enjoyable.

por Wahyu G

10 de Mar de 2018

Not so much different with the materials in the Machine Learning course from Prof. Andrew Ng itself. If you don't have the time to finish the ML course, then you should take this one.

por Akhil

28 de Jun de 2018

A good approach to ML strategy. However, having a programming assignment to better explore results from tweaking models based on the strategies discussed in the course would be great.

por Richard J B

20 de Nov de 2017

Developing intuition on how to structure projects in deep learning is essential to becoming effective and productive. This course is a good start for gaining that experience quickly.

por Iver B

21 de Out de 2018

Valuable information that is well-organized and clearly delivered. Would benefit from a larger number of shorter exercises each week to cement learning after each group of lectures.

por Danielli I

30 de Mar de 2020

This is a great course with excellent contents and guidelines !

Point for improvement:

Please add a programming assignment in python and the questions appearing during the lecture....

por vivek v

23 de Jun de 2019

This course provided an empirical approach in tackling hurdles in solving most common issues faced by data scientist in solving Machine learning problem in a very simplified manner.

por David A N

18 de Mar de 2020

I really appreciate learning about the high level strategies for designing machine learning projects. I only wish there were some programming exercises to put it into practice.

por Søren B

29 de Jan de 2018

Based on my own experience and comments on the discussion forums, I get the impression that the quizzes have a couple of errors in them that makes it impossible to achieve 100%.

por Juan Z

9 de Nov de 2019

This course is less pratical and theoretical. I don't mean it is not helpful to me. I think this course might be helpful as guideline when I hand on the real project in future

por elie a

4 de Nov de 2019

very good course, but I felt like it was lacking one more week of course to get deeper knowledge about how to really get data sets and how to set them up for real applications.

por Christian V

18 de Jul de 2019

you may think because the course is shorter will be much easier but the videos has a lot of information to process. I am excited to tried this techniques on real applications!

por Ambrose S O O

25 de Mai de 2019

A good course. Provided general high level thinking and reasoning for quick problem solving, data management, multi-tasking, transfer learning, and error reduction techniques.

por Sayantan A

22 de Mai de 2018

Not as exciting as the previous courses, but informative nonetheless. A section for handling imbalanced or skewed datasets would be useful, especially for multi-task learning.

por Aleksi S

22 de Fev de 2018

Not as deep into details as the two first courses in the specialisation, but nevertheless I learnt a lot of techniques that I hope will be feasible when I work on AI projects.

por Charles S

28 de Nov de 2017

Excellent lectures and notes as always. Great insights and clearly explained. I think we could have used a programming exercise on transfer learning at least in this section.

por Akanksha D

7 de Jan de 2018

More coding exercises could be included with much more mathematics background explained. Videos could be made a little shorter. There is redundancy in the some of the videos.

por Juan M

4 de Jan de 2018

Good overview of how to structure ML projects with great practical advice. I wish the course had includes a programming lab to help us try out and practice some of the ideas

por Aravindh V

29 de Ago de 2020

Good content. The tips and tricks a experienced AI practitioner has was shared. But at least one programing exercise applying all the concepts learnt, would have been great.