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

4.8
stars
45,255 ratings
5,152 reviews

About the Course

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Top reviews

JB
Jul 1, 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!).

MG
Mar 30, 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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301 - 325 of 5,099 Reviews for Structuring Machine Learning Projects

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 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 27, 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 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 manideep s

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

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 faizy

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

By Fahimul H

May 31, 2020

This was a much needed course after the 2nd one in this specialization! This course provides a clear and essential picture that is needed during development stage as well as shows the scopes of applying different techniques/blocks that were taught in course two.

By Raul T

Oct 9, 2017

Shows methods for improving performance of deep learning setups in a time efficient manner. I like that deciding what to try next for improving a deep learning setup's performance is a recurring topic in Andrew Ng's courses. Knowing this can save a lot of time.

By Tolga B

Jun 23, 2020

Very well structured (pun intended) and informative course! Andrew makes a fantastic job transfering his knowledge to his students. I gained very much insight in general for prioritizing different tasks in machine learning projects and planing the future steps.

By Isaiah A

May 22, 2020

This class, although short, was very interesting and serves as a useful guide to aid in building a deep learning model from scratch. The quizzes are really interesting as well as it makes you think about a step-by-step process in your own model implementation.

By Jay G

Oct 6, 2018

A fantastic course. I believe the strategies presented are practical and powerful in actually developing a deep learning system. I very much look forward to encountering those first problems and using these strategies to guide my model development. Well done!!

By Gillian P

Mar 2, 2018

Great course covering topics that are not seen anywhere esle and are probably highly udnerestimated. The graded simulations are a very good idea that could be used in other courses as well. Professor Ng excellent performance is no surprise for anyone having fol

By Kyung-Hoon K

Nov 23, 2017

This strategic thinking for planning ahead will absolutely save tons of times of ML developers when building a real-world ML system. This course gave me a lot of thinking points, even without programming assignment. Thanks professor Ng, Mentors, and classmates!

By Matthias T H H

Aug 27, 2017

Excellent course on how to analyze errors of machine learning applications. This material provides good ways to improve the speed of iteration over any machine learning project.

This class is unique as professors rarely provide this kind of insights. Thank you!