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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

4.8
stars
49,761 ratings

About the Course

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....

Top reviews

MG

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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.

SV

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This is the knowledge in which we will get from lots of experience only, but the andrew has shared in this course which might help us in future by saving a lot of time through this course experience

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326 - 350 of 5,701 Reviews for Structuring Machine Learning Projects

By Felippe T A

Mar 26, 2020

For me, this is the best course between the first three courses of this specialization. The content here is the fruit of the experience of the professor and can not be found easily on the internet neither in books. Congratulations DeepLearning.ai for this amazing course.

By Rúben G

Oct 13, 2019

I initially underestimate the value of this course. But it turns out that it gives very good insights on how to start tackling a problem with a DL mindset. Also, I learned about Transfer Learning and Multi-Task learning which I think its an amazing plus from this course.

By Elias A

May 27, 2020

Don't let the lack of programming exercises fool you into thinking this isn't as important as the other courses in this specialisation. Professor Ng offers a summary of years of ML experience, as well as a sneak-peek of real world projects and how we should tackle them.

By Jk L

Nov 29, 2017

I want to recommend this course because from it I get knowledge that can explain some of the confusions during my experience of building ML projects. I think in all probability I will encounter much more troubles if I've not got this course. Thanks, Andrew and Coursera!

By Yu X C

Nov 26, 2020

Best course in the entire specialisation in my opinion. Many other courses out there teach the technical aspects of deep learning but this particular course teaches you how to think and make decisions in an actual project which can save you loads of time and resources.

By Sasirekha K

Jun 11, 2019

This course is a fantastic guideline to some very real problems that I am working on in the industry. Thank you, deeplearning.ai team, for breaking down research practices into more definable steps. I already see how I can be more efficient in solving some DL problems.

By Marcel M

Jun 1, 2018

This course is a solid continuum from the first two courses of this specialization. With the added twist of insider information from Prof Andrew Ng, a tried-and-tested practitioner of this Deep Learning art. The Machine Learning Simulation is pure genius! Ahsante Sana.

By Chuong N

Apr 8, 2018

This is the most useful and unique course among all other materials of deep learning. It addresses the problem of trouble shooting for deep learning, which is the most daunting and mysterious. In fact, the note of this class will be a guide line for my future projects.

By John V

May 15, 2021

Excellent course that tied together concepts I know and use in my own work -- how to think about the project, how to optimize your time and resources, how to measure success -- and mapped those to the management of deep learning projects. Very glad to have taken this.

By Amged E

Aug 28, 2020

At first, I was worried because the course doesn't have any programming assignments, but just after finishing the first quiz, I realized that this might be the greatest course I've ever taken in my life (till the moment).

The quizzes were very knowledgeable & helpful.

By Badr B

Feb 9, 2020

Professor Andrew Ng was astounding in the way he explained the concepts, also, like the famous machine learning course, all of the courses in this specializations were great in terms of quizzes and assignments that help have a complete grasp of the subject. Thank you.

By Gerald B

Feb 28, 2018

I enjoy Andrew's approach to managing AI projects. He hits on very real issues we encounter when young, enthusiastic scientists want to solve problems with ML, but get lost in the numbers and multitude of possible next steps to take top improve the quality of a model.

By Daniel F

Sep 28, 2020

Es un curso extraordinario, entrega muchos detalles que hacen ganar destrezas a la hora de entrenar nuestros modelos y el profesor Andrew Ng muestra mucho información sobre su experiencia. Creo que hace un gran trabajo y me siento afortunado de haber pddido hacerlo.

By NiuYaaa

Nov 8, 2017

This course is a little bit hard for me, because I never heard these concept before. But through this course, I got a lot of new ideas to start my own machine learning project, and use these knowledge in practice. Thanks for the nice course and I will keep learning!

By Serkan K K

Feb 2, 2022

Although the topics seem easy, they are very important. It contains important information on how you should spend your money, time and energy most efficiently. Important tips to get started 1-0 ahead when building a machine learning system. Be sure to check it out.

By Alejandro J M R

Sep 10, 2019

Esta fase del curso es de gran importancia para saber como encarar un proyecto de deep learning con sus mejores prácticas. El proceso iterativo de desarrollo es bien explicado y te permite construir la base de cualquier tarea de deep learning que vayas a emprender.

By Simhadri M

Jul 21, 2018

Though we learn different machine learning models to train, we might miss the logical key practices and struggle and waste lot of time while training to achieve better results. This course teaches those important practices to efficiently implement the ML projects.

By naima v

Nov 18, 2017

Very helpful course. This course is very helpful that I got to know the things beyond the technical details of the neural network. About selecting test and dev set distribution, transfer learning, error analysis , end to end deep learning etc. Thank you Coursera...

By 苏高生

Oct 21, 2017

I have learnt algorithms theory of machine learning and how to use them into data mining. However, I’m not good at ML strategy, so I can’t build a very well model. Through this course, I know many methods to improve models which I build before. Thank you very much!

By Mohd F

Jul 23, 2019

Amazing Course ... different structuring strategies involving Orthogonalization, Single number evaluation metric, Carrying out error analysis, and how Cleaning up incorrectly labelled data including Transfer Learning are Beautifully explained by Andrew Ng...KUdos

By Kunal N

Feb 17, 2018

The best part of this course was the "ML Flight Simulator" questionnaires (peacotopia, auto-driving). These real life examples and grading on that is the best thing. It helps you learn and interpret the concepts much nicer. I wish there were more of such examples.

By Anurag A

Sep 11, 2017

This course has been really insightful into how we should work with machine learning projects. True, that most of the ideas discussed here are not covered in normal university curriculum. Thanks a lot to Professor Ng for coming out with this really helpful course.

By AJAY G

Sep 27, 2020

According to me, It is a very good course. In this course, they have taught about what can be the best practice to handles errors in the projects. They have taken different scenarios and gave us what can be the best choice that you can take to handle the problem.

By Akshat J

Apr 11, 2020

Once a person has a knowledge of how to become a developer in the prevoius courses, this course gives you the knowledge to escalate from developer to a project architect. It teaches crucial techniques required to guide the training model to produce better result.

By Selim R

Nov 19, 2017

I feel this is an extremely important course for all aspiring deep learning practitioners: being good is not only about knowing the algorithms and architectures, but also how to best manage your time and choose the most promising avenues to explore. A rare course