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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 40,629

О курсе

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Лучшие рецензии


11 дек. 2019 г.

Great Course Overall

One thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.


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.

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576–600 из 5,361 отзывов о курсе Convolutional Neural Networks

автор: Joshua B

26 мар. 2018 г.

Dr. Ng did a superb job going through the history of ConvNets. The examples, applications, and homework were wonderful, and I feel now much more skillfully able to read the scientific literature on the subject.

автор: Raj

29 нояб. 2017 г.

Perhaps the best course so far (course 5 is not out) in this specialization. I wish we got to train one of the CNNs and not have to use pretrained models but given the time and data needed, it's understandable.

автор: Gonzalo G A E

15 июня 2020 г.

Great course. One of the best of the specialization. Contains a thorough "theory" description of Convolutional Neural Networks as well as some pretty cool applications, and useful links to the original papers.

автор: Milton M

5 июня 2020 г.

A good compromise for someone new to computer vision. It covers almost everything you need to apply CNNs to real life applications, with a good balance between implementation details and theory under the hood.

автор: Sanket D

29 мая 2020 г.

Interesting SOTA ideas like CNNs, ResNets, object detection, etc are taught in a very intuitive mannar!

This course brings in an interest and lights a spark of the interesting things Deep Learning can perform!!

автор: Alok R S

9 авг. 2019 г.

This course of covers almost every aspect of convolutional neural netwoks. There are proper hints in the programming assignments so that one can easily start with convolutional neural networks.

автор: Stephen S

21 окт. 2018 г.

So far, this was the most useful and my favorite course of the series. Convolutional Neural Networks are really incredible study and have many useful features that you can implement to solve your own problems.

автор: Naveen D V

6 дек. 2017 г.

This course has demystified the concepts of image recognition through a systematic breakdown of the main steps involved. It is very encouraging to learn algorithms that have been developed in the recent years.

автор: Neelkanth R

17 июля 2022 г.

I usually don't write reviews but I think it's helpful for the future learners to decide whether this course is worth investing money and time.

I would HIGHLY recommend this course, and i cannot stress enough!

автор: Govind S

26 июня 2020 г.

This series is a gem. Although, I have build some Deep Learning Models, this course provided me an in-depth knowledge of 'What, How and Why'. It enhanced my theoretical underpinnings of learning astoundingly.

автор: Juan-Pablo P

1 июня 2020 г.

A very good deep overview of 2D convolutions (and extensions to 1D and 3D) with real applications to object detection, face verification and recognition as well as neural style transfer. I fully recommend it,

автор: Sarwar A

7 мая 2020 г.

A great course taught by a great personality. It was very much exciting to implement some of the challenging as well as the exciting applications of deep learning like face recognition, object detection, etc.

автор: Aishwarya R

23 апр. 2019 г.

Excellent course. Learnt not only about ConvNets but also about how to learn further after the course ends and apply the knowledge in practice. Thank you Dr. Andrew Ng and all other members of

автор: Akash S

14 апр. 2019 г.

had a lot of fun in this course, i would, recommend every student to take up this course as it gave me an insight on how human eyes process images. this also helped me a lot to understand deep learning better

автор: Jonathan L

18 дек. 2018 г.

Great lectures on Convolutional Neural Networks and their role in computer vision. The course could use more lectures on using tensorflow/keras as someone new to those modules may feel a little lost at first.

автор: Matthias P

5 апр. 2018 г.

This was really fun. Great explanations from Andrew and engaging programming assignments.

A few hick-ups in the assignments here and there, but the community/moderators are extremly helpful!

Great experience!

автор: PLN R

17 мар. 2018 г.

Amazing course, as far as course is concerned! Faced certain issues with the grader software; but it has nothing to do with the course content which is probably top notch! Looking forward to the final course!

автор: Carlo C

15 апр. 2020 г.

Very very happy to attend this course! Andrew NG is always the best and explains always real well ! The exercises are useful and help to understand better the concepts. Very fascinating course! Thanks again!

автор: Christopher

12 апр. 2020 г.

An excellent introduction to CNNs. Of the first 4 courses in the Deep Learning specialization, this was the most challenging, and had a number of great practical examples of CNN applications, including YOLO.

автор: Enrico C

2 апр. 2020 г.

A great introduction to CNN, probably the best you can find on Coursera. I recommend using the message board where mentors will help to get to an in-depth understanding of what discussed during the lectures.

автор: Libing z

18 дек. 2017 г.

It's a perfect course.

Andrew shows what CNN is, how it works and why it helps.

Andrew also show many case studies to make me understand the concept better.

The homework is really good to help me understand CNN

автор: Daniel G - O

9 мар. 2019 г.

Very good content, but assignments have minor issues when sending for grading. These issues shouuld be pointed because sometimes the answer is correct but the grammar not and this is evaluated as a 0 grade.

автор: Amit P

31 дек. 2018 г.

Very happy with the course - CNN was a concept I had heard a lot about and this course provided everything I needed to know to understand it in detail and implement it. Thanks Andrew for making this course.

автор: yi-chun t

29 сент. 2020 г.

The instructor is the best among all instructors that I've had so far. The program assignments are great in terms of giving enough instructions and guidance to help students complete complicated homework.

автор: Mushfiqul A

20 авг. 2020 г.

Brilliantly designed course in its entirety. Learned loads from it and hoping to apply in projects soon. Can't show enough gratitude to the designers and of course the instructor, Sir Andrew Ng. Thank you.