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.
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.
por 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.
por 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
por 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.
por 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.
por 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.
por 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.
por 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!
por 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.
por 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.
por 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.
por 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.
por 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.
por 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.
por 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 !)
por 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.
por 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. :)
por 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.
por 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.
por 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.
por 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.
por 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.
por 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.
por 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.
por 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
por 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.