Chevron Left
Back to Structuring Machine Learning Projects

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

4.8
stars
49,925 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

TG

Dec 1, 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.

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:

1151 - 1175 of 5,724 Reviews for Structuring Machine Learning Projects

By Quan D

•

Aug 22, 2017

I've joined ML projects, I also made some mistakes like what mentioned in this course. this course really helpful to me, Thanks a lot,

By Arun P R

•

Apr 26, 2020

Best course to know more insights about ML projects and how to manage it. It got lot of insights about real life ML project problems.

By Tanbir S

•

Mar 31, 2020

The course content is not what I expected. It surprised me pleasantly. It was filled with a lot of practical strategical suggestions.

By Somashekhar H

•

Oct 25, 2019

The Course given how to distribute the Dataset into Train,Dev,Test. It also explains what to do when the bias and variances are more.

By Mun T Y

•

Aug 30, 2019

Excellent case study walkthrough to really make us think into the machine learning projects and what are the best approaches to them.

By Sonny R

•

May 26, 2019

Great job showing us how to guide and direct our projects in the face of avoidable bias, variance, and varying data sources. Thansk!

By Avijit K A

•

Dec 9, 2018

Often it is easy to get lost when fixing/improving your system. Here, it makes things concrete as to which direction to move towards?

By Mengfei W

•

Aug 30, 2018

Even though it feels very high level at first, it actually gives us clear directions when handling deep learning problems in reality.

By Wei-Lin C

•

Aug 26, 2018

Its better to create a folder for all lecture notes! thank you. The contents are really interesting and easy to catch the concepts :)

By Akshat J

•

Aug 15, 2018

If you want to learn how to work on real life projects and how to tackle problem you face during that this course is perfect for you.

By Óscar V

•

Dec 3, 2017

This course has been, so far, my favourite. What a great experience; generalizable not just no ML project but to projects in general.

By Clinton K

•

Nov 21, 2017

I like how this class teaches you not only how an ML pipeline works, but also how to apply it to real life problems. This is awesome.

By Nafiz I

•

Aug 16, 2017

A fun glimpse into the mindest necessary to implement machine learning projects in practice, something not usually found in pedagogy.

By Chandan D

•

Jun 26, 2021

This course helped me to learn strategies to take wise decisions to improve your ML & DL models and hence made me a better engineer.

By Puran D

•

Mar 28, 2021

This course is very helpful in making decisions in distributing dataset. It is also helpful in reducing time in training iterations.

By Piyas C

•

Aug 17, 2020

This course is excellent for the basic knowledge of the structured machine learning and thanks to Prof. Andrew for amazing lectures.

By Guillermo

•

Jul 24, 2020

Great course that shows you the global picture of a Deep Learning project, and teach you to focus in the metrics that really matters

By Sebastian J

•

Jul 18, 2020

Fantastic course as per the description, the flight simulators targeting ML are well structured and the instructor is simply superb.

By Norelys R

•

Feb 14, 2020

Although you won't write code. This course teaches multiple and necessary techniques very useful in a real problem. Very interesting

By Shah M D

•

Jun 4, 2019

Andrew Ng has really put down all his wisdom in this course. Great course for doing machine and depp learning in RealWorld projects.

By Balint M

•

Oct 10, 2018

I think this course is very valuable also for managers who don't work on ML projects as a daily routine, but lead such developments.

By SHANKAR K

•

Mar 11, 2023

Excellent course for solving real-life problems using theoretical knowledge. Both weak assignments are outstanding and mindblowing.

By Zeeshan G

•

Feb 8, 2021

excellent course, i have been teaching ML for number of years, it answered most of questions i had accumulated over number of years

By Manuel R

•

Oct 17, 2020

Great course, there are some topics that Andrew explains that you can only get by experience, and he's able to share it. Excellent!

By Ahmed S (

•

Aug 29, 2020

i love how the quizzes were structured , they were fun and challenging at the same time they made really take in what was explained