Chevron Left
Back to Structuring Machine Learning Projects

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

4.8
stars
49,631 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

AM

Nov 22, 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.

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.

Filter by:

226 - 250 of 5,688 Reviews for Structuring Machine Learning Projects

By deepak v

•

Jan 6, 2018

Looking at the title of this course I predicted that it will be regarding to teach me how to organise the source code files of ML project and more specifically how to build a ML project and components of deep learning project but it was all about DEBUGGING ml project so for me this was in off beat course from its title.

By Tony H

•

Aug 30, 2017

Extremely useful, practical techniques for deep learning projects. I feel much more able to construct my own neural networks, diagnose and solve issues with them after following this course. Professor Ng is a gifted teacher. His style is careful, methodical and never less than very well prepared and deeply enlightening.

By Ayan G

•

Apr 20, 2020

Its really nice to get the valuable insight of managing an AI project, this course not only thought us about deep learning, but also how to manage them efficient and take smart decision. I like the concept of Transfer learning as it can same a lot of efforts and time to build an system for complex. Thank you very much.

By Kwan T

•

Oct 1, 2017

I am very lucky to be able to learn from Andrew the DOs and DON'Ts of how to develop a successful practical deep neural network for real applications. It would take a machine learning developer many years of working experience to acquire any one of the topics that Andrew articulated in this course. Thank you so much!!!

By Adam F

•

Nov 1, 2021

I completed the entire specialization and having nothing but good things to say. Highly recommend it! Lectures are engaging, and Andrew does a fantastic job explaining some very complex topics. Programming assignments are challenging in a good way. You’ll really feel like you’ve learned a lot by the time you’re done.

By Konstantinos K

•

Dec 31, 2020

The course is great. It tackles a lot of problems regarding strategic decision making and at the same time important concepts such as human-level error, avoidable bias, transfer learning, end-to-end deep learning and others are being taught. The questions/exercises really test the core concepts that are being taught!

By Mark Z

•

Jun 11, 2019

I've decided to take this course after seeing its feedback from other people and the comment which got me was the following: "This course is could be summarized as a machine learning master giving useful advice". I think it perfectly describes the course's content. This course is definitely worth investing time into.

By Dunitt M

•

Feb 10, 2019

Excelente curso, muy recomendado para quienes tienen una idea de Deep Learning pero con frecuencia se encuentran en situación que no saben cómo afrontar o cuál camino intentar primero. El conjunto de habilidades impartidas aquí no te harán un mejor programador, pero te ahorraran muchas horas de esfuerzo innecesario.

By Gaurav M

•

Sep 7, 2017

Amazing tips shared for structuring machine learning projects, which were ignored in most of the other ML books. Building a model is one thing, but tuning it to make it work better in the real world is more important which this course focuses.

Thanks Prof. Andrew Ng for the consistent support of spreading knowledge!

By Muhammad A

•

Aug 13, 2020

Although, this course of specialization was simple with no assignment still the case studies were quite informative. I would suggest to include a case study related to google machine learning for navigation and voice recognition. We youth can easily relate to this case study. Overall this course was a full package.

By Yuezhe L

•

Nov 19, 2018

This is a very helpful class. I have been working on machine learning projects for years. This course provides methods to systematically trouble shoot problems in a machine learning project. Despite all the samples are using neural networks, the methodology can be applied to improve other machine learning projects.

By Danial A

•

Jan 3, 2021

Andrew NG has a peculiar style when it comes to teaching data science. I have never seen someone explaining the terms this effectively. The material in this course is a direct revelation of his years of experience and entails the unique feature of being the lessons learned from the experience. Really great course.

By Bernard O

•

Oct 24, 2018

Excellent course on managing through the thick of bias/variance tradeoffs. Been doing a lot just based on things I have picked up through experience, but this course puts a the quantitative rigor and discipline behind the art. The sections on transfer and end to end deep learning were eye opening sections for me.

By Gema P

•

Feb 25, 2018

This course is strategically very important so congrats on making it

I would add a programming assignment including transfer learning or multi-task learning implementation due to the multiple cases of use that are today in the industry.

Thanks again for making this Wonderfull material available to the community ^^

By BAZIL F

•

Dec 29, 2019

Very useful course for understanding nuances of AI and different useful techniques in strategizing the approaches. Extremely useful in architecting, designing and delivery of the complex solutions involving AI (even as a sub-component). Prof. Andrew Ng is always a pleasure and honor to learn from. Thank You Sir!

By Harvey Q

•

Sep 4, 2017

Really inspiring course, and UNIQUE. No other class, I think, provide these suggestions on the big question "what's next?" in ML projects. The videos are a bit weirdly sequenced. But they provide very systematic ways of project starting, data splitting, model evaluating, problem finding and tuning. Great course!

By Pedro B M

•

Feb 28, 2019

This a course on key practices one should have when developing a ML project. Once again Andrew Ng is very pedagogical, teaching sometimes complex concepts in a easy to understand and practical way. I particularly liked the case studies, where the learned concepts had to be put into practice for decision taking.

By Niyas M

•

Oct 29, 2017

What a great session! Full of practical advice and strategies to help you iterate fast. Prof. Andrew draws on his years of hands-on experience at top companies to put together the best practices for structuring your machine learning projects. This has been the most valuable course in this series for me so far!

By Nikhil K

•

Jul 9, 2020

super helpful! something that's really valuable in-terms of optimally organizing the thought process i should use to approach an issue i want to solve with Deep Learning.

also, the Quizzes in this course (in-particular) were very important for me because it helped ingrain the tenets of this course in my mind.

By Zebin C

•

May 18, 2019

In the course, I learned how to divide train set, dev set, and test set, and how to solve the problem of different distributions of train set and test set. Impressive is the transfer learning. Transfer learning is a very effective way to help me provide a completely different approach to solving new problems.

By Swapnil T

•

Mar 31, 2020

What can be better than this, a highly qualified and passionate individual explaining what he has observed and learnt from the mistakes of other professionals , those who themselves are one of the smartest brains so that we don't make mistakes or waste our time realizing that we were hitting something wrong.

By Jeel R

•

Jan 16, 2022

It was really helpful to get the knowledge about, how difficulties are tackled when working on real project. As sir said in the starting of the course, otherwise it would have taken 2 years to gain all this knowledge. This course helped me a lot about how to pursue certain approach while handling a project.

By Hardik G

•

May 14, 2021

A very useful and important course for this specialization. Downloading datasets and simply applying machine learning algorithm is not the right way. The quality and distribution of data along with the requirement of the project has to kept in mind and this course gives the perfect intuition about the same.

By Jiri L

•

Jan 4, 2021

This is a really good course and material applicable to deep learning and, to an extent, also to machine learning. The course gives you a very good diagnostic and problem solving methodology for various issues with algorithm performance. So far I'd consider this to be the best course in the specialisation,

By Vishnu V

•

Mar 8, 2020

Excellent course to understand the ML project pipeline and then to analyse the various problems that could pop up during an ML project. The tips and tricks that we obtain from this course to address those problems are really valuable and unmatched. It is truly one of its kind course from the master itself!