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

47,357 classificações
5,435 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

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.

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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4701 — 4725 de 5,397 Avaliações para o Structuring Machine Learning Projects

por Nick R

7 de Jan de 2018

Informative, but theoretical. After 3 courses I'm looking to do some hands-on work of my own.

por Bobby

24 de Out de 2017

Lecture was good but no programming assignment for this course. I took out one star for this.

por Ramachandran C

12 de Out de 2019

Loved the practical guidance provided by Andrew Ng on large-scale machine learning projects.

por Arthur J

20 de Jul de 2019

It would be great to have some materials to be able to go back to once done with the course.

por Kyle S

23 de Out de 2017

This is a great course. It will be an invaluable reference when tackling real-world problem.

por Yang Z

20 de Out de 2017

Some videos don't end properly and instead give you a black screen to stare at for a minute.

por Akhtar H

9 de Fev de 2021

This is little bit tricky course. But main understanding comes when you solve case studies.

por Neel K

19 de Out de 2020

It was better to include some more case studies. This was a better real-time understanding.

por Michael L

10 de Jun de 2020

Sometimes, the explanations/advices given were too lengthly and contained some repetitions.

por Amielle D

24 de Jul de 2019

There were some typos throughout the course, but the core topics were still discussed well.

por Tariq A

12 de Jan de 2019

A good quality course, would have loved to have some programming exercises to go with this.

por Ankur K

13 de Nov de 2017

It would have been a little better if some assignments were also provided with this course.

por h_st

1 de Ago de 2021

It was really nice. Maybe some more hints could be given. I missed my own programming ;-)

por Rohini H

9 de Jun de 2020

still with some more example & more simplest way to solve them .with simple basic examples

por Martin B

17 de Mar de 2018

Again, excellent, but proof reading of the test and proof-viewing of the videos is needed.

por Sudeep K

7 de Abr de 2020

It could be more detailed. More Code intense! However, the course was really informative.

por Abhishek P

24 de Set de 2019

Initially a bit hard to understand but repeating the session helped to grasp the concepts

por Pedro L A V

26 de Fev de 2018

Good course, but there are too many small topics in each week and no hands-on assignment.

por Blake C

20 de Set de 2017

Not quite sure, but there are some problems in exam. Hopely fix them as soon as possible.

por Bharat M

24 de Jul de 2020

A good theoretical course to help remember the nuances of how to structure a ML project.

por Vikas C

20 de Jun de 2019

It was a nice course, it can better if some demo codes are used as an example separately

por Shuo W

3 de Jan de 2018

Pro: useful practical suggestions;

Con: language used in quiz should be further polished.

por Ridvan S

15 de Out de 2017

"Chillout course", but "test-by-real-cases" is very exiting and very fine idea. Strong 4

por riad s

21 de Set de 2017

I wish there was some practice assignments related to the concepts learnt in this course

por Vinay K

5 de Fev de 2020

Info about the approach in applying DL/ML concepts to various scenarios were explained.