Jul 15, 2019
Dear Andrew! Thank you so very much for making me belive in myself as a machine learning engineer. Your lectures & excercises are like "shoulders of Giants" on which a good student can stand out high.
Jun 30, 2018
Very good course to start Deep learning. But you need to have the basic idea first. I would suggest to do the Stanford Andrew Ng Machine Learning course first and then take this specialization courses
von Vishnu J•
Jul 22, 2018
The intro course has been a phenomenal experience learning. The concepts were clearly explained along with derivations. I thank Coursera, Andrew Ng and all others who were involved in this for taking this massive step in teaching deep learning and AI. I would be happy to take more practical oriented courses under this banner especially computer vision, NLP, AI in specific. Another suggestion from me would be to include lessons on building neural networks from libraries like tensorflow, pytorch, keras etc.
von Martin V•
May 02, 2018
Very helpful course. Great, well prepared assignments! Even without python knowledge I was able to code essential parts of algorithms. Practical assignments were really good reward at the and of each week and a motivation for me to keep going. You will not be forced to learn python in parallel but occasionally I have to read library reference guide to debug. I also installed python locally to test syntax and get more in, but it is not necessary, provided python jupyter notebooks is also usable for this.
von KHANH V•
Nov 13, 2017
Thank you for the easy-to-follow content. The explanation about back propagation in details is great. The Python code is elegant and should be a good starting point for learners to make more progress in expanding it.
Some time assignment submission gave errors even there is no problem with networking issue. This definitely need to be improved, or learners need to resubmit many times.
If you need translation of the course to Vietnamese language, let me know. I will do it for free, for my Vietnamese students.
von Brandon E•
Sep 10, 2017
A great introduction to neural networks! The videos and assignments were helpful, and the repetition helps things sink in. I would've preferred more mathematical rigor and a little less hand-holding in the assignments, but I understand that this course is meant to appeal to a wider audience and it does a good job of being approachable. I particularly enjoyed the weekly "Heroes of Deep Learning" videos, and tips and pros/cons of studying machine learning in industry vs. academia. I'd recommend this course.
von César J N R•
Aug 23, 2017
It is a relly nice course, well explained as Andrew Ng. has always done. Because it is still a new course, there are few erratas of course, but those are being already corrected. I suggest a lot to take the Machine Learning course by Stanford University here on Coursera first, unless you already know about Neural networks, since sometimes there are things that you should know. These kind of courses have made me going really deep into Data Science and I'm quire sure this specialization will help. Thanks !
von Subianto W•
Jun 10, 2019
Excellent class, wonderful instructor and extensive practice problems. The theoretical explanations on deep networks are very thorough with the math behind it. Unlike other deep learning courses that take shortcuts with using pre-made keras or pytorch libraries, this course went through the math behind the functions and then went on to build them with python from scratch. The exercises are also well prepared with clear notes and test functions to make sure the codes work as intended. Highly recommended!
von Yu S•
Feb 11, 2018
I hope instructor could fix the notation in back prop. I think this should be easy, because he just need to stick a red color comments beside in the video.
One big misleading is by back prop:
Because the notation for back propagation algorithm presented in the lectures treats dA and dZ differently from dW and db(I ignored layer l index in my notation). Namely, 'dA' and 'dZ' are always computing the derivatives
dL/dA and dL/dZ
respectively, but 'dW' and 'db' are computing the derivatives
dJ/dW and dJ/db.
von onkar p•
Nov 28, 2017
Again an awesome course ,hats off to NG for this brilliant series of courses.
One thing which i liked so much was the interview session with Ian ,Peter etc.Came to know about further research and development going in Field of ML & DL.
i liked the way Ng has put up the lucid explanation of vectorized implementation and how to do random initialization.
And the ending was super with DNN for image classification.
Its a good experienced learning so far with Prof Andrew.
Thanks & looking forward to next course .
Aug 18, 2017
I took Andrew's Machine Learning course but was never able to complete the course. This time I have completed this course and hope to complete the remaining 4 as well.
Andrew has been very successful in developing the intuition for the neural networks and once it becomes intuitive it's all imagination.
I loved all the interviews with "Heroes of deep learning". To be honest, I never knew about any one of them prior to those interviews. It is great to know the best people in the industry.
Thank You Everyone
von Omar Z•
Jul 31, 2019
a basic course, given the depth of mathematics it discusses. One good thing in the course is the frequency of the practical assignments, however, I feel the course needs one small project where each student writes the whole program on his own to get used to the whole process, rather than just implementing the functions. One thing I believe needs to be added, is to offer hints as an Optional thing, so that some people feel challenged (as well as grasping the idea in a deeper way hehe) during the course.
von Rúben G•
Oct 01, 2019
I am software engineer looking to expand my skill set to cover Deep Learning. I first learned that Andrew NG was a big reference on AI when I read Life 3.0. Then I searched about him and found he has a DL course on coursera and so I didn't even hesitated. This is my first course in Coursera. I found the classes super smooth to follow as Andrew NG introduces the topics in a very easy to understand way. I am super excited to cover the next courses. Thank you so much for sharing your knowledge this way!
von Rehan S•
Aug 24, 2019
Beginner friendly course. This is Andrew's Ng first but very important course and that is prerequisite of next courses of same specialization. Assignments are well designed by instructor very helpful to understand the
theoretical material. Assignments designed according to real world problems like image classification. Well effort by instructor that makes easy all the difficult topics for us and thanks to coursera team that providing us such a great platform where we learn something new at any time.
von Kiran W•
Jul 30, 2019
Professor Andrew Ng's teaching style is simply amazing! I was able to absorb the material fairly quickly and reinforce my learning with very well structured exercises. I, now, have the confidence that Deep Learning is no rocket science. It is pure mathematics and art at play! If your algebra fundamentals are in place and you are creative, there is no better path to AI than Deep Learning. Believe me, when you start "getting" DL concepts, it quickly grows on you and you are addicted to its philosophy!
von Melissa C•
Jul 09, 2019
So happy I completed the first course in the series of Deep Learning. I got a great foundation for how neural networks work, with good instruction, good illustrations, and plenty of resources. The lab notebooks are particularly well-written, with thoughtful instruction and step-by-step application of what we learn each week. Outputs have "expected" outputs shown below, so you know if you're on the right track or not. Overall very happy with this course. It's a good bit of work, but so worth it.
von Tanmay K•
Feb 28, 2020
An excellent that covers the fundamental required for deep learning. Professor Andrew Ng gives an excellent intuition behind the inner workings of deep learning and practical guides for implementation with the help of the assignments. I found the heroes of machine learning section to be the icing on the cake as it gave a broad overview of the latest developments in the field of deep learning. To anyone who wants to get an insight into this wonderful domain, I would definitely recommend this course.
von Robert G•
Jun 12, 2019
Terrific intro to neural networks! The instruction was very clear on the steps that made up NN/DL algorithms and very easy to follow. I really liked how the programming examples were explicit in what made up the algorithms, and then there were test cases for each section of the code. This made it easy to step-debug through the code, rather than waiting until the code is complete and running into a bug and having to try and trace back through the entire notebook. Thanks for putting this together.
von Glenn B•
May 31, 2018
Great topic, well organized, and very understandable. Tests and assignments are structured very well and are completely doable.
I get the dynamic aspect of writing the lecture notes in the videos, however the lecture notes should be "cleaned up" in the downloadable files (i.e., typos corrected and typed up). Additionally, the notes written in the video could be written and organized more clearly (e.g., uniform directional flow across the page/screen rather than randomly fit wherever on the page.
von weonseok c•
Mar 15, 2020
Although there are many pre-written codes, I think this course gave a good and easy image how neural net is confirmed and works to a beginner.
Some more things I also wanted are explanations or texts for how to prepare datasets (image data, in this case), and some other usages, not just distinguishing images but sounds or texts and so on too.
But maybe image is most easy example for a person who really don't know well about math or program. I still want to get next courses for further study.
von Subhadip M•
Oct 25, 2019
Extremely helpful course. I got a good and depth knowledge about the Neural Network, Activation Function, Vector and Matrices, Forward and Backward propagation, Parameters and Notation. The main thing I love with this course is the implementation of theory and examples practically on the code. While you are going through the course, I will suggest you to take notes and revise it again and again. Otherwise, you will definitely confuse in many portions of the course. Thanks to Professor Andrew Ng.
von Herment G•
May 06, 2018
This course is amazing. Andrew is an amazing teacher, you can see that he loves explaining this topic and understands it very well so he know how to put things simply. You may feel lost from time to time but the things that you may hardly comprehend are consistently reminded throughout the course. This gave me a great insight into the field of deep learning and I'm looking forward to learn more about it. I highly recommand this course to anyone who has basic coding knowledge and interest in AI.
von Michal S•
May 18, 2019
This was a very enjoyable course! It was very practically oriented, so everyone with some basic knowledge about machine learning, programming and neural networks could complete the course without too much of math background. I know this may seem as a disadvantage as well, but I think having good chance to do cool projects (because the programming assignments are cool) can motivate to further study of presented papers and textbooks well and eventually maybe use the concepts in research or work.
von Juan R C C•
Sep 14, 2017
After complete the Machine Learning Course, this one has been more easy to complete than it and, thanks to Python programming, easy to align with other related courses where there are programming assignments.
In addition, it's a pleasure to follow trainings delivered by Andre Ng. His teaching quality is outstanding.
The only "but" is that I missed to use DNN with multiple classification and not only binary classification. Probably it will be covered in next courses into the specialization.
von Maciej B•
Aug 19, 2017
Course is nicely constructed. If you have 2-3 days without other commitments (I didn't) you can finish it very fast including all the - non-required - computations on paper. Coding excersises are well designed although not very demanding. Additional, more complex (bonus) excercises would for a nice add-on to the main course.
The only problem I have with the course is that I must wait 4 weeks for the next step, despite finishing the first stage during the first week. I do not understand why.
von Fernando D G•
Mar 04, 2018
I can not express the amazing professor Andrew is. He is capable to explain complex concepts in a way anyone could understand.
I would also like to say that the assignments of this course are amazing. They have taken a lot of time to create the Python notebooks and to match every single line of code with what was showed in the lectures. It's almost impossible not to get confident with Neural Networks after you have completed all of them.
My sincere congratulations to all the teaching staff.
von Joyce G•
Jan 21, 2018
Absolutely wonderful! I have strong math and CS background. I can see this course can be learned by many people from many background.
VERY helpful. I cannot say enough good things about it! Thank you so much!!
The only one thing is that it will be great if the homework assignment deadline can be even more flexible. I work full time and I have a big family. I have been working holidays and weekends to get the course done. It will be nice if the deadlines are more flexible for people like us.