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

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46,916 classificações
5,382 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.

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.

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4651 — 4675 de 5,334 Avaliações para o Structuring Machine Learning Projects

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 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.

por Vishal G

19 de Dez de 2019

Interesting course, but all this could have been summarised in the first course itself!

por Hao W

16 de Jun de 2019

This course is not so well organized as the previous two. Everything else is very good!

por donato t

15 de Jun de 2019

Very valuable insight in real world usage of DL and guidance in approaching DL projects

por Wilson L

16 de Set de 2017

It would be even better if there are more quiz and assignments made in ipython notebook

por Takshshila R

1 de Jul de 2020

This gives subtle but important knowledge

about training with different distributions.

por Rohit G

26 de Mar de 2020

The pacing was a little off, and perhaps some code would help. Otherwise, pretty good.

por Kirill S

29 de Fev de 2020

Useful and short course, but with a lot of information repetition. Could be optimized.

por Ashraf A

16 de Nov de 2019

Very helpful in understanding the way the machine learning projects should be managed.

por Dominik F

25 de Jul de 2019

Very useful, but some questions were misleading or were not discussed until next week.