Chevron Left
Back to Structuring Machine Learning Projects

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

4.8
stars
49,809 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

ED

Invalid date

Excellent start for digging into topics that are not taught nowhere else. The author books 'Machine Learning Yearning' is a great next read that goes deeper in some of the aspects, really recommended.

MG

Invalid date

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:

2776 - 2800 of 5,709 Reviews for Structuring Machine Learning Projects

By Kees v d T

•

Feb 20, 2020

Very usefull for stucuring machine learning projects

By 홍진우

•

Dec 7, 2019

지금까지 들은 세 강의중에 최고의 강의였습니다. 실무에 많은 적용을 할 수 있을 것 같습니다.

By Tamás K

•

Aug 5, 2019

Great material, for me it was too verbose in places.

By PK M

•

Jan 8, 2019

Great insights on real-life problems faces with NNs.

By Andrei V

•

Aug 24, 2018

Great way to get a glimpse of a researcher's work :)

By Mirzodaler M

•

Apr 30, 2018

Very interesting, useful and helpful course. Thanks!

By afshin m

•

Feb 6, 2018

Excellent information, most useful during a project.

By Manuel Q

•

Dec 28, 2017

Brilliant course as all Andrew NG courses use to be.

By 刘晓鹏

•

Nov 3, 2017

Andrew Ng老师通过这门课系统化的传授了，在项目中会遇到的实际问题，让大家少走弯路，节省宝贵的时间

By Yan L

•

Oct 28, 2017

very helpful for constructing a deep learning system

By Farrukh

•

Oct 23, 2017

Amazing insights, some which can save months of work

By RobinChan

•

Sep 6, 2017

Useful suggestions for MLers who are doing projects.

By Suraj J

•

Feb 4, 2024

Concepts were explained in an easy-to-follow manner

By Prashant S

•

Jul 19, 2023

one of the most elaborate and well explained course

By Tobias L

•

Aug 26, 2020

Great course, focusing on the bigger picture of ML.

By Caroline W

•

Aug 2, 2020

The course is useful, and the teacher teaches well.

By Shankar M

•

May 6, 2020

Wow! Any machine learning beginner would love this!

By Diego M

•

Apr 24, 2020

Gives production experience to a junior AI engineer

By Han-Chung L

•

Jan 25, 2020

The insights provided by Prof Ng is second to none.

By MIGUEL A Z G

•

Jan 23, 2020

Those case study were awesome! totally recommended!

By Jorge M G O

•

Jul 28, 2019

Thanks, I learned a lot of things with this course.

By Anand V

•

Jul 26, 2019

case study is great. That helps to think strategy.

By Shail R

•

Nov 14, 2018

Excellent insights based on significant experience.

By Peter S

•

Nov 10, 2018

Very useful. Liked the case study type assignments.

By Daniel L

•

Jun 24, 2018

Great course with some useful tips for practical ML