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

4.8
stars
38,840 ratings
4,257 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.

MG

Mar 31, 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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201 - 225 of 4,221 Reviews for Structuring Machine Learning Projects

By Neil O

Dec 08, 2017

This is a unique course that provides invaluable perspective on how to direct a deep learning project. Its value is derived from understanding the performance metrics ( the data about the data) and acting in a data driven way. Anyone in charge of a deep learning project should take this class.

By Mahmoud S

Oct 23, 2019

It has the best practice tips and top secret advises for Machine learning.

It really simple and clear. I love it too much.

Especially, the exams, A lot of effort is done on it. And the instructors notice which best way to absorb this deep concepts in this course by flight simulation techniques

By Virendra K Y

Apr 05, 2020

Thank you so much team and NG sir. What a simple explanation of everything. Love you guys and god bless you and your team sir. Honestly, no word to say how simply NG sir explains all the concepts. Hard work team. Love from India. and do yoga to boost your immune and stay safe from Covid19.

By Charles B

Jul 21, 2018

Covers some interesting points, particularly around introducing external data to your training set that doesn't match the distribution of the dev/test sets. Andrew Ng offers practical advice for running projects using Deep Learning techniques and how they differ from traditional approaches.

By Tanay G

Feb 04, 2020

I was sceptical at first, it seemed that the course would just teach a lot of theory which won't be relevant. I am happy to say that I was wrong, the course gave me a better understanding of how to take various decisions for a particular machine learning problem. I liked this course a lot.

By Akash B

May 14, 2019

It teaches the decision making process whenever you're working on a real- world probelm. You should grasp all the ideas into your brain very well. I think this is very important as per in the field of deeplearning.

This course is very rare, and it provides best case scenarios to test with.

By Haoxuan Q

Jan 26, 2018

I love this course very much and I would strongly recommend this course to other DL colleague. It is truly that DL is a highly empirical process which needed to be more systematic. In this course, I have learned many methods to make DL more controllable and predictable. Nice Job! Thanks!

By Pedro f

Mar 23, 2019

In my experience with Machine learning, we usually spend more time checking the algorithm than checking the best distribution of our data. In this course, Professor Andrew teaches us the need and obligation to create a correct distribution of our data with examples from the real world.

By Mohd S A

Feb 28, 2018

Extremely helpful for a beginner so as to think like a machine learning problem solver. I think there should be more quiz added to this course with scenario like given in two quiz. I have never enjoyed any course so much by taking same quiz again and again to get better understanding.

By Hiep P

Dec 14, 2017

In the bloom of Deep Learning/Machine Learning industries, know how to build a project is more important and a priority to know what knowledges to build that project. Break the problems, take each step follow the guide and avoid common pitfalls in process, this course will satisfy you.

By Javier H E T

May 01, 2020

this is definitely the best course i had taken. it has just 2 weeks, but it was the hardest. i will definitely come back to see the teachings here explained to check up if i'm thinking correctly so i don't make much mistakes in taking a direction in projects.

definitely recommended!!!

By Elena P

Sep 01, 2017

The case study format for quizzes was highly effective in helping me uncovering gaps in my knowledge that I didn't know were there. I would have liked to see at least one more case study per week. One per week just wasn't enough.

Overall good course with a few minor video glitches.

By Carlos A B R

Jul 22, 2019

I found this course really interesting because it gives many details on what path to follow to achieve better results not only depending on the amount of data we have but also taking into account some small details that can make a difference when starting machine learning projects.

By Dharam G

Jul 02, 2018

A very well systematic approach explained, to structure ML projects.Can be grasped and implemented by anyone, let it be a beginner or some expert.Really liked the idea of case study in quiz. (Wait ! How about extending this idea into some coding exercise ? Would be some real fun !)

By Andrew M

Oct 11, 2017

There is no coding in this course, but you learn a lot of how to design a Deep Learning Study. I learned a lot about the distribution of Training/Dev/Test sets and how to diagnose problems when a neural network is not performing as well as anticipated or if it is performing well.

By Tyler K

Aug 28, 2017

Outstanding course. Many of the points made in this course mirror the hard earned knowledge I gained back when I worked on Dynamic Rank search engine focused neural networks.

This may end up being my favourite of the 5 courses but let's see if the last two have more math first. :)

By Alexios B

Aug 20, 2017

This part of the specialization is short but it includes a lot of valuable information. Many of the tips are quite basic engineering best practices which most engineers should find natural, but some are very specific to deep learning and these are particularly useful to newcomers.

By Brad M

Aug 22, 2019

This is truly some information you'll never get in a standard class setting; this is more similar to compiling years of ML experience into short packets of advice that will guide your decisions for years to come. Extremely helpful, and recommended for all deep learning engineers.

By WALEED E

Jan 17, 2019

This course is really what any PhD would need to conduct his research in more time saving and efficient manner. It would be great if coding was accompanied (even if only running and watching results) to touch all aspects of analysis and suggested improvements could be visualized.

By Aditya V B

May 18, 2020

One of the most important course in this series . This course actually helps you visualize the problems and standstills you might face when you are working on a model in real life. It also talks about practical solutions to improve your model that are valuable in the tech world.

By Debojyoti R

Apr 30, 2020

An unique course. I don't think such a course is offered by any MOOC. I would suggest every DL enthusiast to take this course.

The programming assignments are very challenging. It forces us to think abstractly to find solutions encountered during real life Deep Learning problems.

By Maksim P

Apr 26, 2020

Despite this course is labeled as basic level, it contiains very useful information related to strategy of developing ML projects. And use cases prepared by prof. Ng and his team is what you will get only by practice. It really helpful to structure what was learned by this day.

By Karthikeyan R

Dec 19, 2019

A great insight into how to improve the performance of the deep learning system without having to actually spend long hours/days and working on real project. Learnt a lot in improving the model's performance and where to look for the errors and how to invest time in debugging.

By Douglas H H H

Sep 22, 2017

I totally agree with your flight simulator analogy. This really helps me to learn your experience in practising machine learning knowledge; which otherwise I need to spend many years of doing "try and error"

Thank you very much for your kind sharing of your practical experience

By Wade J

Feb 26, 2018

As always, very well structured material considering the nature of the content and trying to make it understandable and make sense. I also appreciate that it is rooted in real-life experience which serves to make me pay really close attention to everything that is being said.