Chevron Left
Back to Structuring Machine Learning Projects

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

4.8
stars
45,317 ratings
5,160 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

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.

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!).

Filter by:

426 - 450 of 5,105 Reviews for Structuring Machine Learning Projects

By Farhad A A

Oct 27, 2018

'Structuring Machine learning Projects' is a strategic approach to modeling machine learning algorithm. And this is the course that really teaches how we can apply ML algorithms we learnt to the real world problems "Efficiently".

By Bonnie M M B

Mar 11, 2018

Loved the Course, it really Helps a lot for the Projects, You save us lots of time.

I have a question which activation function did I have to use on the final Layer on a Multi-Task problem, Im working in a project with multi-task.

By Derick N T

Oct 5, 2020

The simulator exercises are particularly interesting, as the introduce learners to making decisions when dealing with machine learning projects. This was the highlight for me, and I believe, it has help me build some intuitions.

By Sushil S

Nov 17, 2019

Everyone, literally everyone who wants to start doing machine learning projects at the industry level should first go through this course. I think this course will make the life of an fresh machine learning engineer much easier.

By snehil v

Jun 12, 2018

I have studied Deep learning in detail from free courses but tried this course by Andrew and loved it because it was great for people who are being introduced to deep learning projects.I will recommend this course for beginners.

By K V P

May 27, 2020

This course is really a deep insight of practical application. Completing this course gave some important points ,but they can be truly learned only when we try real world application by our own. Once again thank you Andrew sir

By Sven S

Jul 25, 2019

Again, the videos were very informative and pleasant to watch, using well established didactic methods. Information given were (as far as I am aware) up to date and pretty good to understand. Thanks for the excellent lectures.

By Abiodun O

Mar 14, 2018

This course is really short but very packed. Prof. Andrew shared alot of his practical experience in this course. Given the value of Prof. Andrew's years of experience, this course will still be "cheap" even if it costs $ 1000!

By Amit T

Oct 22, 2020

This course teach you strategy which will help you in solving real time problems and reference have been taken from real problems. it gives you a prospective to weights different option and create your strategies. Good work !!

By Mohamed A A

Dec 21, 2020

This course containes precious insights regarding right strategies and tactics to use in order to build a sucessful machine learning system. Thank you for the great effort put in preparing this remarkable source of knowledge!

By JAGRUTI P

Aug 18, 2020

This course has really taught how to start solving a real-world machine learning problem, what to do incase of facing different kind of issues. Hopefully, I will be able to apply them in designing machine learning algorithms.

By Girish G

May 3, 2020

This particular course details all the minute aspects needed to have a better model. All the concepts were explained clearly in the course. I felt this course to be a like a "icing on the cake" to basic Neural Network course.

By GUSTAVO E Z

Mar 6, 2020

Once more Andrew is greaqt teachng and very clear in his explanations. This course let me learn how to improve the development of a Deep learning project aiming at the right parameters and algorithms to be worked on the road.

By 吳沛燊(Pei-shen W

Aug 31, 2017

Very useful ! It is a common problem of getting lost in ML projects, although the guidance seems abstract at first glance, it proves to be invaluable when ever we are in the midst of struggling for better modeling performance

By Gudivada R K

Jun 21, 2020

Much needed course for those who are in their starting/middle stages of DL/ML projects. This course gonna play a vital role in their projects. The explanation from Andrew Ng was interesting with real-time scenarios examples.

By Gourav K

Aug 22, 2019

Thank You, Professor Ng, for creating so much valuable learning. The values to those are added and we get ambitious and inspired being through the interviews you took with great Deep Learning and Machine Learning scientists!

By David C

Jul 11, 2018

I came into this course with the bias that it would be the least applicable of the five in the series-- however, I really feel that the information conveyed was extremely important for practical application of deep learning.

By Salim L

Mar 25, 2018

Really helpful project strategy for Deep Learning that can save many months of work. While this course is a bit repetitive at times, Andrew Ng's recommendations are hugely important and his simulation tests quite innovative.

By Marko N

Aug 26, 2020

Pretty interesting ideas on how you can improve your deep learning system. It teaches you a number of strategies that help you identify the most promising things to try. Quizzes are especially interesting in this course.

By Sanket D

May 25, 2020

In depth learning of most sought and required concepts and giving insight on how to structure a ML project from scratch practically. The quizzes are just wow! They give a very good insight of how ML projects are structured!

By Justin K

Apr 27, 2020

Short course with no programming exercises, but full of good information that is immediately useful such as where your time will be best spent depending on situations you're likely to encounter in pretty much every project.

By Aloysius F

Mar 20, 2020

Excellent, this really goes into the nuance of successfully executing a project. Setting up an initial system is not that difficult. Understanding the sources of error a systematically resolving requires judgment and graft.

By amin s

Jul 26, 2019

This course is great. Recommend it to anyone working on Deep Learning projects. Saved me lots of time, and taught me how to systematically think about my problem and opened new windows to improve my network. Thanks, Andrew!

By Sean C

Feb 15, 2018

This was a valuable stepping stone in applying Andrew Ng's other teachings to realistic scenarios. The "simulators" were actually a great representation of realistic machine learning project issues & potential resolutions.

By Kurt K

Nov 27, 2017

A clear explanation of a difficult subject with an emphasis on being able to create and to understand your own neural networks.- Plus in this module how to allocate your resources so you can achieve a successful project.