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

4.8
stars
48,213 ratings
5,530 reviews

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.

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2551 - 2575 of 5,497 Reviews for Structuring Machine Learning Projects

By Siddam M S

May 2, 2020

Machine Learning strategies, development and training set

By C.K. T

Apr 15, 2020

Love the "flight simulator" exercise. Great way to learn.

By Zhi L

Mar 17, 2020

It's really exciting that AI get better and better today!

By Shashank C

Apr 11, 2019

The course was very useful for me, thank you Prof Andrew!

By John G

Feb 1, 2019

Excellent for technical aspects (wich is very important!)

By HOA N

Oct 7, 2018

absolutely, this is a very useful course for ML projects.

By 朱欣宇

Sep 13, 2018

It really gives me a lot of inspiration,thank you Andrew!

By liyimeng

Sep 1, 2018

Very useful principals in building a deeplearning network

By Sumit K

Aug 16, 2018

Excellent course with one of the best faculties available

By Amine H

Jan 19, 2018

Learned A Lot!

Thanks for sharing your experience with us!

By Sekib O

Dec 19, 2017

Really nice tips and tricks directly from the ML experts!

By Yang X

Nov 26, 2017

Thank you Andrew! you make me love deep learning so much!

By Berker K

Nov 2, 2017

Made me think many aspects of real life scenarios! Great!

By James T S

Oct 19, 2017

Superb course that includes valuable practical knowledge.

By Salma E

Sep 13, 2021

Very helpful, especially when it comes to error analysis

By Nhut D

Aug 10, 2021

Give you great insight into the building a model process

By ruchi m p

Jul 29, 2021

Very good explanation and best practices has been shared

By Moritz K

Jan 10, 2021

As usual a really nicely structured course by Andrew Ng!

By induraj

Jun 6, 2020

Exceptional Course. Thank you Professor Andrew and team.

By Syed T S

May 21, 2020

As usual Andrew NG at his best. Very informative course.

By Timur B

Jul 11, 2019

Lots of useful advice on how to proceed with ML projects

By John H

Jul 11, 2019

excellent class and I especially like Andrew's teaching.

By Naman S

Jul 4, 2019

A must course for anyone who is studying deep learning .

By Ivan M

May 24, 2019

Important topics that everybody skipped, awesome course!

By Satheeshkumar M

May 4, 2019

Great course to learn practical nuances of Deep Learning