3 сент. 2020 г.
Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.
1 сент. 2019 г.
This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.
13 нояб. 2019 г.
Great course. I would suggest updating the libraries and thus the code since they are very old. When trying to run code on my computer I faced a lot of broken code due to differences in libraries versions.
автор: Rizdi A R•
22 апр. 2021 г.
The course delivered is meticulously organized, plus how it works in the view of mathematics . The way Andrew NG describing the networks added with some real cases makes the learning enjoyable. Thank you.
автор: Javier C N•
2 сент. 2020 г.
In depth approach to a very complicated subject. Resources are amazing and as usual, Andrew Ng provides world class lectures. I always find myself amused by Andrew's very down to earth manner of teaching.
автор: Seth B•
11 мар. 2020 г.
One of the most interesting and challenging courses I've taken so far. The assignments for this course are awesome and practical, with great visuals. Style transfer and facial recognition are really cool!
8 февр. 2020 г.
Again, good starter-level course. You can gain a big picture of CNNs through this course, but you have to do many others things before you can really do something with them. I will take CS231n after this.
автор: Dimitry I•
25 июня 2019 г.
Another great course in the in the Deep Learning specialization. Lots and lots of data is presented in small steps that make it easy to assimilate and apply. Thank you to Prof Ng and the rest of the team!
автор: ignacio v•
5 окт. 2018 г.
Andrew Ng must be the best teacher in all the moocWorld !
Great course, great practices
We only need a Reinforcement Learning course from him and, thus, a Deep Reinforcement Learning to infinity and beyond!
автор: Frantisek H•
4 сент. 2020 г.
Excellent course - Andrew's teaching is what's so needed in the machine learning community. He explains concepts properly so that one truly understands them, and thus knows what to do when applying them.
автор: Hind A b•
27 мар. 2020 г.
very informative course with real life applications. the explanation is very clear and i really enjoyed doing the practical assignments. the only downside is that choices on quiz is little bit confusing.
автор: Joaquin T•
25 мар. 2019 г.
Superb course on CNN by Andrew Ng. Video lectures can be daunting at some points, mostly because of its dense theoretical content, though it provides a great background on how to start working with CNNs.
автор: Smriti P•
10 мая 2018 г.
It is definitely a must for people who are new in this field and are interested in Deep Learning field. Gives you an insight into how CNN actually works and how anyone could take it to further improvise.
автор: Abdullah A M•
16 дек. 2017 г.
this is really deeeeeeep. among all 4 courses till now it seemed to be hardest one to me as well as most conceptual too. Thanks Andrew sir and Coursera for such a wonderful opportunity to learn about CNN
автор: Βασίλειος Ν•
8 июля 2021 г.
Very good course. You understand how convolutional neural networks work. The amount of code you need to write is relatively small, and so this does not make the course intimidating, and it flows easily.
автор: Pawel S•
11 авг. 2020 г.
It is a great course, more interest than the previous in the specialization, but also more challenging. The best part of this courses are projects, face recognition is only one of the engaging projects.
автор: Octav I•
23 дек. 2018 г.
Great lectures, really well explained, assignments have a good balance for such a hard topic. Maybe another short intro/ optional assignment on keras generic model/layers/activation approach could help.
автор: Simhadri M•
18 авг. 2018 г.
Doing this course will help you understand the core concepts of CNNs clearly. Andrew has discussed most of the implementations that are widely used today. The Citation of papers and authors was helpful.
автор: Vitaly C•
21 мая 2018 г.
The course is great, very good try to present CNNs as good as possible. The assignments grader behavior sometimes is strange, I would like to ask to check it and fix to prevent learners unusual efforts.
автор: Jan Z•
7 янв. 2018 г.
Awesome content, teaching very recent methods in an understandable way. Programming exercises are very well documented and fun to solve. Thanks for putting this course together deeplearning.ai, big fan!
автор: Alessio D M•
9 дек. 2017 г.
A very good course. Not too technical, but it provides you the tools and overall understanding framework to dive deep into convnets. As any other Andrew Ng's courses, I highly recommend taking this one.
автор: Uğurcan A•
21 мар. 2022 г.
I am here again 3 years later. This course is really great. Even though I have gained much experience in deep learning and computer vision. I still use Andrew's advices. Thanks for this great resource.
автор: Jianxu S•
6 июня 2020 г.
Another excellent course on deep learning of Convolution Neural Networks (CNN) widely used in computer vision, including easy to understand lectures and hands-on exercise with commonly used frameworks.
автор: Rooholla K•
5 мар. 2020 г.
I found this course extremely constructive and it was so cool to participate in a course where the instructors had put the materials and the assignments just in a right and logical order of difficulty.
автор: Fotis T•
7 апр. 2021 г.
Very good introduction to programming convolutional neural networks. Although the models and functions needed are complicated ,this course takes you by the hand and introduces to all these wild ideas
автор: John J M•
20 сент. 2020 г.
Excellent, solid insights into working of models as well as providing references to the original work. THe assignments give practical examples of models one might want to implement for their own use.
автор: Switt K•
11 окт. 2020 г.
Andrew still teaches great!
The programming exercises sometimes have trouble with loading databases (sometimes takes like 10 minutes to complete loading), and the kernel sometimes crash for no reason.