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

4.8
stars
46,916 ratings
5,382 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.

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.

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5176 - 5200 of 5,334 Reviews for Structuring Machine Learning Projects

By C. I

Aug 17, 2017

Very short, not many practical examples. Lots of repetitions.

By W S

Aug 31, 2019

Video lectures tend to be repetitious, and can be confusing.

By Anthony M

Oct 23, 2017

Practical knowledge, but I would prefer more hands on coding

By Jiheng R Z

Sep 9, 2017

Quite a few errors and ambiguities in the practice problems.

By Zingg

Nov 16, 2017

The topics are interesting however the content is off par.

By Axel G

Jun 14, 2020

Good content, but very focused on Computer Vision and NLP

By Daniel D

Sep 4, 2017

The course es good, but it seems still under development.

By Juan A C A

Aug 30, 2017

It would be better if you include programming exercises.

By Abdullah M

Jan 13, 2018

It was hard to keep interested - lost focus many times

By Brandon C

Dec 6, 2018

lacking in the usual engaging programming assignments

By Varun S

Sep 23, 2018

Was expecting more scenarios for real data experience

By Jian Z

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ppt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

Sep 19, 2018

The course is OK, but it lacks programming exercises

By JETTIBOINA V N D S R P

Jul 20, 2019

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

By Tzushuan W

Jun 1, 2019

Wordy and too abstract without hands on experience.

By Evgeny S

Apr 5, 2018

I would rather expect a course more like a capstone

By Mirko R

Jan 4, 2021

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

By Rishab K

Apr 25, 2020

a assignment could be given along with the theory

By Eric H

May 17, 2021

Very little content. Everything was common sense

By shafkat r

Dec 24, 2019

More programming exercises would have been great

By Beatriz S M

Feb 14, 2018

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

By AKUT J R

Aug 16, 2020

Nice module however some repetition of content!

By Mikhail G

Oct 31, 2017

quite short, would be nice to get some practice

By Paavan G

Sep 19, 2020

Could have included some programming exercises

By Thomas A

Mar 26, 2020

Interesting but not very straight-to-the point