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

4.8
stars
50,119 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

YP

Jul 26, 2018

Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN? ?? ???? ??? ???? ???? ? ??? ???? ??? ?? ?? ???!

SB

May 7, 2020

This course gave some very useful tips on how to start with a Machine learning project when I was struggling to do so. It also gave useful information about error analysis and data set distribution.

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5576 - 5600 of 5,746 Reviews for Structuring Machine Learning Projects

By A M

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Jan 14, 2018

It was hard to keep interested - lost focus many times

By Brandon C

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Dec 7, 2018

lacking in the usual engaging programming assignments

By Varun S

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Sep 23, 2018

Was expecting more scenarios for real data experience

By Jian Z

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Nov 6, 2017

个人感觉课程的内容比较难于理解，希望老师在设计辫辫迟方面能给出一些完整直观的解释，有的时候书写会不是很清晰

By Bogdan P

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Sep 19, 2018

The course is OK, but it lacks programming exercises

By JETTIBOINA V N D S R P

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Jul 20, 2019

Learned new things but the course was boring.......

By Tzushuan W

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Jun 2, 2019

Wordy and too abstract without hands on experience.

By Evgeny S

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Apr 5, 2018

I would rather expect a course more like a capstone

By Justin C

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Oct 22, 2022

Quiz questions are too vague. Need more clarity.

By Mirko R

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Jan 5, 2021

It's been overall useful, but it's not "hard" ML.

By Rishab K

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Apr 26, 2020

a assignment could be given along with the theory

By Eyüp ?

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Jun 11, 2023

Some questions in the last quiz was quite vague.

By Eric H

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May 18, 2021

Very little content. Everything was common sense

By Md. S R F L C

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Dec 25, 2019

More programming exercises would have been great

By Beatriz S M

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Feb 14, 2018

Very general, I would like to be more specific..

By AKUT J R

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Aug 16, 2020

Nice module however some repetition of content!

By Mikhail G

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Oct 31, 2017

quite short, would be nice to get some practice

By Yabo L

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Mar 7, 2022

The problems in quiz are like game of wording.

By Paavan K G

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Sep 19, 2020

Could have included some programming exercises

By Thomas A

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Mar 26, 2020

Interesting but not very straight-to-the point

By Marco A L H

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Sep 24, 2018

not as fun as the other courses of this series

By Manish S

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Apr 10, 2018

Content was not enough to create a new course.

By Edward W

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Oct 24, 2017

Expect more hand-on code practice or more quiz

By Allan Y

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Mar 30, 2018

Should not be a separate course. Too general.

By Adam S

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Dec 27, 2017

Some useful insights but not much depth here.