23 de ago de 2021
This is a very good course for people who want to get started with neural networks. Andrew did a great job explaining the math behind the scenes. Assignments are well-designed too. Highly recommended.
6 de jul de 2018
I think the course explains the underlying concepts well and even if you are already familiar with deep neural networks it's a great complementary course for any pieces you may have missed previously.
por Christian B•
24 de ago de 2018
This is really an excellent course. In particular the notebooks are very well done. I passed the course but have to admit that I still need to go back to be fully clear on the dimensions of the vectors and matrix as well as how all the helper functions we implemented play together. But this is what I was looking for. An example where you really get through the network development and understand step by step what is happening. Thank you Andrew and team. I am looking forward to the other courses of the specialization.
por Yash P•
2 de dez de 2020
It's the easiest to understand course for deep learning by Andrew Ng. Deep Learning is my goal, and I wanted to get started with it from the most basic things. The instructor has done it very nicely that an absolute beginner could get started with DL, having some basic programming skills and high school math. I loved it and strongly recommend it to the high school students like me who want to learn Deep Learning. I am very thankful to Andrew Ng and deeplearning.ai for making it a lot easier than what it looks like.
por Roudy E•
5 de nov de 2020
A very elaborate course. It is also very practical and hands-on with its programming assignments. You will learn al the theory behind neural networks and how they work and you'll get the chance to build your own from scratch (without using Keras + TF which hide everything behind the scenes). Also, all the proven math functions that will be used in the implementation is also supplied to you during the assignments so you don't have to be an expert in calculus in order to obtain the required equations and derivatives.
por Nitesh S•
1 de out de 2020
The course has been designed brilliantly with not just easy to understand lecture material(and hands-on Python based labs) but also very practical and informative interviews with some of the pioneers in Deep Learning domain. It's worth every minute I spent on it. As always, Prof Andrew and his teaching staff managing the discussion forums are very knowledgeable, well-read and (most importantly) eager to help others learn. Thanks Coursera for approving my financial aid so I could finish this extraordinary course! :)
por James T•
9 de jun de 2020
Great course! Super clear and easy to follow lectures and assignments. Love that we learned a thorough mathematical basis for almost everything behind deep learning (other than some complicated derivatives). I would gladly recommend to anyone trying to learn the basics of deep learning. The programming assignments were also incredibly convenient (Jupyter notebooks in browser), though it might help to give students a quick intro on debugging in Python (I was already familiar with ipdb and used pdb in the notebooks).
por Vishal M•
12 de out de 2019
It's the perfect course to start with understanding of neural networks. The way the concepts are explained, multiple times starting from shallow level to a deep level and are converged at the right place is amazing. The quizzes and programming assignments are well structured. The course spans over 4 weeks but can be completed in couple of days. The programming assignments are hand-held with lots of documentation and hence reprogramming the assignment without the jupyter notebook is recommended post the completion.
por Agile B•
10 de out de 2018
The teaching of Andrew NG is very educational - he builds all the necessary information about calculus into the lectures step-by-step, and repeats the confusing notation syntax over and over. This gets almost seamlessly translated into the programming exercises. Only on rare occasions, the python code is not updated, e.g. it misses the ravel() transformations required for some variables. Overall, this course deserves a sixth star for super good integration between the theory videos and the programming assignments.
por Dietrich B•
28 de set de 2018
A very enjoyable and effective introduction into Deep Learning! The most important concepts are first introduced and immediately after practised to program your own simple Deep Learning Networks. Interviews with some of the most famous Deep Learning practitioners help to put the learned material into context. The only thing which I could imagine to make this course even better would be a written summary the student could print out to have the material available for later use and repetition. Highly recommended!
por Kiran R•
2 de jun de 2019
Great foundational course. A minor feedback - the crux of the programming assignments are the way we should approach structuring the problem (including defining helper functions, etc.). Perhaps the assignment could be further broken down (as an optional exercise) where the student is made to come up with the design choices for the functions as well. This will help students gain a great understanding of the various blocks that go in building these models, which will be helpful when they do it for themselves later.
por Mohammadreza M•
26 de dez de 2019
Thanks Andrew. I really enjoy this course. Although there are plenty of knowledgeable lecturers in Coursera, a few of them know the teaching skills like Andrew. I specially took your course since I had taken Andrew's ML course in 2013 as well, and I knew how patient he is and how well he can teach to anybody with different level of knowledge. Assignments were challenging but clear. The checkpoint helps a lot and make sure learners if they made a mistake, they would not lost. Merry Christmas and Happy New Year <3
por Laurence G•
4 de ago de 2019
Really good course. Andrew is clear, and provides a great introduction to structured deep learning. I feel that some extra videos showing the full calculus behind back propagation would be helpful for those who want it. However these can be found elsewhere on the internet if you look around. Assignments are pretty good, with a few things I would nitpick - however as long as your methods return the correct outputs, you can rewrite the internals as you desire. Heroes of deep learning extra videos were interesting.
por Jensun R•
4 de set de 2017
I've taken other machine learning courses before and I was somewhat familiar with neural networks before taking the course. The error backpropagation technique was something I couldn't get my head around intuitively. But, after finishing the graded exercises in this course, such ideas are well cemented in my mind. Andrew does an excellent job of controlling the mathematical jargon from overwhelming beginners. I would definitely recommend this course to anyone who wants a hands-on experience with neural networks.
por Teshome D T•
1 de jun de 2020
In my honest opinion, I found this course to be extremely well organized. The concepts put forward are done so in a manner that does not overwhelm most of the students but it also provides just enough challenges to those of us that are interested to further explore the algorithms and the mathematics behind them, if need be.
Andrew Ng is by far my favorite educator of all time and I feel truly blessed to live in a time that allows me the opportunity to learn from the wisdom and know-how of such brilliant minds.
por Li T•
24 de set de 2017
Definitely a satisfying course for beginner. If you don't have any experience on neural network and deep learning, this is an excellent place to get started. Videos are great with full explanation on topic and Professor Ng keeps telling "don't be scared by math or python notations". I spend about 6 hours for first coding assignment and learned a lot on details to get thing right. After that, I just feel much better on following assignments. Cannot wait to start course 2. Thanks everyone to provide this course!
por LI H•
19 de ago de 2017
Fantastic course. Andrew has always been instructive and can explain complicated things in a simple way.
The assignment codes are very well structured and with the skeleton outlined it's not that difficult to finish the homeworks. But building from scratch is another level of challenge and I'll try that after the course.
Also the back propagation mathematical induction is not covered here. The math part is also good to learn when I have time, but I guess I'm more interested in the application of Deep Learning.
por shaila a•
11 de jul de 2020
I am a fan of all courses delivered by Andrew Ng. This one gives a thorough understanding of shallow and deep Neural Networks. After the course, you can be sure to have a sound understanding of how a model is built from scratch. The assignments are also organized in a way to reduce your effort on redundant tasks like creating the structure of functions. The focus is only on having you write the code that tests your understanding. I really enjoyed this course and I am looking forward to the next one. Thanks :)
por Wilson C•
14 de mai de 2020
Following the lectures and completiong quizzes and programming assignments puts the student through rigorous math, the math in the course is overwhelming at a college math/engineering level - but as the student continues throughout the course, the redundancy of theory does get absorbed and by the end of the course the student develops a solid understanding of the course material. The programming assignments implement full scale deep layer neural networks with practical applications to illustrate the concepts.
por Tag J•
22 de ago de 2018
This was an amazing with a lot of new and interesting things to learn. I am really glad that I decided to take it. Its approach toward neural networks is quite easily understandable and allows oneself to use those concepts as he wishes. The programming assignments are a really big help as well. You can learn all the math but without the programming skills, there is hardly any point in doing deep learning. A special thanks to Prof. Andrew Ng. I was already a fan, but this course was just amazing. Thanks a lot.
por Hari S•
19 de nov de 2022
Excellent course if you want to understand deep learning at a high level without delving too much into the math. This is exactly what I wanted because I am an engineering manager who has to make decisions about ML/AI. I have a math background and can see how some of the math works, but what I wanted was a more visceral sense or intuition about deep learning, and this course is perfect for that. The math actually gets in the way, and Prof. Ng very cleverly kept the focus on the intuition rather than the math.
por Kai-Peter M•
28 de out de 2019
Great course!!! The best online course I have ever taken! I enjoyed almost every day I participated in that course, really an educational treasure! It is so comprehensive and detailed at the same time. Due to the good presentation of the topics it was really understandable. The only thing I would wish for future participants: please make it easier to get the complete Jupyter notebook environments from the Coursera platform once completed. I spent a lot of time here - even after consuming the related blogs.
por Vishnu J•
22 de jul de 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.
por Martin V•
2 de mai de 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.
por KHANH V•
12 de nov de 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.
por Brandon E•
10 de set de 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.
por César J N R•
23 de ago de 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 !