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Learner Reviews & Feedback for Structuring Machine Learning Projects by deeplearning.ai

4.8
31,213 ratings
3,281 reviews

About the Course

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Top reviews

AM

Nov 23, 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.

WG

Mar 19, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

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101 - 125 of 3,242 Reviews for Structuring Machine Learning Projects

By Shehab A S

Nov 06, 2018

This course helps me to learn a lot of things to consider while developing a Machine Learning based system which are very necessary. That was a great experience.

By Jun W

Nov 06, 2018

Nice overview of things you need to consider before starting and during ML projects.

By Tejas S S

Nov 08, 2018

Definitely should not overlook this course. It may seem small, but provides the insight needed for major projects. Consider this as precious gems of advice that you should follow like the law!

By Kryštof C

Nov 07, 2018

It is very good probe to practice. I would very appreciate to take this course before I have started in machine learning. It would help me to realize some mistakes I have maid before. On the other hand, for people, who have some experience with machine learning, some chapters are being over-explained, as the topics are quite clear to those people. Overall: I would recommend this course to everyone, who wants to start with his/her own NN training.

By kapil

Nov 22, 2018

As per me this is the must do course for any ml enthusiast.

By 谢宇敏

Nov 24, 2018

I like it

By fabrizio f

Nov 23, 2018

Very good. Would have appreciated even more practice quiz.

By Suresh S

Nov 22, 2018

This course is as equally important as understanding the nuts and bolts of the algorithm proper.

By Laurence C

Nov 24, 2018

Fascinating strategic insights

By Avni G

Nov 23, 2018

Superb take-aways. Im sure this course knowledge will help me build solid models. Thank you Andrew and Team!

By 李子龙

Nov 24, 2018

really good lesson,thank coursera and deeplearning.ai

By Man M S

Nov 08, 2018

Great Tips & Techniques to improve the ML Algorithms

By Brian ( B

Nov 09, 2018

learning strategic thinking of managing a machine learning project and some tips on performing model diagnosis.

By Veeresh S

Nov 10, 2018

Excellent course

By Michèle W

Nov 10, 2018

Learned a lot.

By twice154

Nov 08, 2018

very good course

By Ashit G

Nov 09, 2018

Thanks to Andrew Ng, who has put his all experience of problem solving in this short course.

By Jhon S

Nov 26, 2018

cool

By Javier O

Nov 25, 2018

Very important common practices in ML, especially the tips of error analysis and ways to solve very common problems.

By Jabberwoo

Nov 26, 2018

Great course!

By Rajnish C

Nov 11, 2018

Most important learning is on how to make acceptance matrix and validation matrix and setting goal for team. And most importantly error analysis and strategy for improvement.

By Jérôme C

Nov 11, 2018

Very rare and good insights into the real problems faced and the right thinking framework to go about them.

By Peter S

Nov 10, 2018

Very useful. Liked the case study type assignments.

By mvpzhao

Nov 12, 2018

very good, thanks Andrew Ng

By WENNI l

Nov 12, 2018

This course is very practical oriented