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學生對 deeplearning.ai 提供的 Convolutional Neural Networks 的評價和反饋

4.9
39,874 個評分
5,271 條評論

課程概述

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....

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AR
2020年7月11日

I really enjoyed this course, it would be awesome to see al least one training example using GPU (maybe in Google Colab since not everyone owns one) so we could train the deepest networks from scratch

RK
2019年9月1日

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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101 - Convolutional Neural Networks 的 125 個評論(共 5,243 個)

創建者 Luis E R

2019年4月3日

Andrew's teaching is exceptional, he finds the right way to convey the necessary information for complex concepts, he does not skip them but strikes the right balance of not going too deep, however he does warn you in a way, that you need to study them on your own.

I think the course, will give you very strong foundations if you take time to understand what you are really doing and what the algorithms are doing.

After this I think you will require a lot of practice with several examples on you own,

創建者 Rujuta V

2020年8月23日

This course provides a detailed explanation of what are ConvNets. Further it also discusses real-life applications of Convolutional Neural Networks . The programming exercises which includes Face Recognition, Object Detection and Transfer Neural Networks are extremely well-designed and helps to code the above problems using tensorflow framework. I found this course extremely valuable and fun to learn and helped me a lot in improving my skills. Thanks @AndrewNg for this wonderful lecture series.

創建者 Hari K M

2018年1月18日

Really good course but relatively tougher than the previous ones. Learnt a lot with best part being able to learn state of the art algorithms and implementations. Did felt kind of oblivious at times while doing the programming assignments but the discussion forums came in handy during those times. There are some issues with the grading of last programming assignment which I think will be resolved soon. I definitely recommend this course to everyone who wants to specialize in neural networks.

創建者 Dhritiman S

2017年12月9日

The material in the course was very good. Andrew Ng is a fantastic instructor and is able to convey concepts in the most intuitive way.

This course would be perfect, but for the problems with the last two assignments (Face Recognition and Style Transfer). There were errors in instructions and grader solution wouldn't match solution expected in the notebook. The only way to figure out how to pass the assignments was to dig into forum posts where information was provided in a haphazard way.

創建者 Paulo A F

2017年11月9日

Great course. It has all the main state-of-the-art approaches. I just missed dealing with 3D data (RGB-D and point clouds). I believe the programming assignments get better as the course progresses because they get more demanding.

This is a great overview course. I suggest anyone interested in deep learning vision to start with this course and then move on to implement a CNN in tensor flow form scratch using one of many tutorials online.

Thank to the team for this great course!

Best regards,

創建者 Matei I

2019年3月3日

A lot of quality content in this course. The first half focuses on the intuition behind ConvNets and their implementation, while the second half focuses on applications. I thought that the neural style transfer application was particularly enjoyable. My only suggestion for improvement is to let the students do more work in the assignments for the last two weeks. I feel that most of the code in these assignments was black boxed, and I got to implement a minimal portion of the algorithms.

創建者 Martin B

2019年9月1日

As with all the other courses by Andrew Ng, pacing and presentation are perfect. Learning this material is highly rewarding. Programming assignments are clear and accessible, although a little bit more thorough introduction in the use of Keras and Tensorflow wouldn't hurt in some cases. I found myself pretty deep in the documentation of both libraries - although that might be part of the intended learning process. Highly recommended! - Thanks to professor Ng for making this available

創建者 CAMILO G Z

2020年1月14日

Curso excelente. Da todos los detalles más importantes sobre redes convolucionales, incluyendo las matemáticas que las hacen funcionar (incluso explica backpropagation en un ejercicio opcional) y cuáles son y cómo funcionan las aplicaciones más importantes. Omite una que otra cosa, por ejemplo cómo aplicar vectorización a todos los ejemplos de entrenamiento, y de vez en cuando durante los videos secciones de audio se repiten por alguna razón, pero mayormente está bastante completo.

創建者 Mihai L

2018年2月19日

This course is still amazing. Finally understood what CNN's are for and how to use them.

This is the first time in deeplearning.ai specialization that I had to consult the forums. by far implementing in low level code convolutions (first asignment) was the most difficult part.

Spent more time then with the other courses but it was time well spent. Again Andrew NG delivers a good course.

The minor editing problems in videos are the only issue that might be raised with this course .

創建者 Li M

2021年5月31日

I'm so suprise that the equitment was applied by this course. As the course progress continue, I found the calculation consumption amoung the coding assingment became exponentaily increase ,so I just checked the GPU inside the Coursera Jupyter Notebook, I found I'm using the Telsa V100 !! That is absolutely gorgeous especially the price of the GPU has been soaring along with the cryptocurrency.

No wonder why each epoch of the Cost function and the gradient decent can be that fast.

創建者 Andrew K

2017年12月29日

The entire course is great, from the lectures by Andrew Ng, to the homework assignments, and the TA's help on the forums. The really terrible part of the course is the coursera grader, which I had to hack for 3+ hours just to pass an assignment. I dont wanna dink the review for this because the class itself is wonderful. But please fix those technical issues. So the 5 stars come from averaging 10 stars from the course itself, and 0 star for coursera technical issues. :-)

創建者 Sergey K

2021年2月1日

thank you for such a comprehensive introduction to field. I cannot wait to start my own projects. I believe that wouldn't be possible without the boost given by this course.

I advice everyone interested in the field (and new to it) to take this course, this is worth and absolutely covers everything you need to know to start solving a certain kind of computer vision problems on his/her own.

appreciate everything what the Team has already done and still doing. thank you again

創建者 Omar S M

2019年9月16日

This is an excellent course in which Professor Andrew Ng explains the concepts of convolution, pooling and convolutional neural networks very well. Also the various advanced convolutional network architectures and various applications in computer vision are discussed in an excellent manner along with references to the research papers on which the content is based. The programming assignments are also excellent and really help you learn the principal concepts and techniques.

創建者 HEF

2019年6月2日

Before taking this course, I thought computer vision had a difficult learning curve. After taking it, I found that many difficulty materials are omitted so that I could learn without too much pressure. While I could still look into algorithm details because many papers are recommended. The programming assignments cost me a little more time than the previous courses, but bring so much more fun! I felt quite proud of myself when I successfully built the CNN in my assignments.

創建者 Meng K

2020年12月31日

The lectures taught by Mr Andrew are very clear and understandable, which really helps a beginner like me a lot in starting the journey to learning CNN. Besides that, the labs also provide more explanation on top of the lectures while providing the chance for students to gain practical knowledge in actually implementing the CNN. Overall, the pace of the learning is manageable, not too hard for beginners but also deep enough to really understand the workings behind CNN.

創建者 Ashwini J

2020年1月1日

Thanks to Andrew Ng and team for putting together great content around Convolutional Neural Network. This is a fairly complex course, I needed to go beyond content provided in this course, specifically around understanding dimensions resulting from a convolution operation applied on an input image. This could be because it is hard to imagine a 4-d object. Otherwise, good content put together, assignments are good and useful starting point for projects in actual practice

創建者 Shyam C N

2020年5月17日

This course was one of the better ones in the specialization. I enjoyed it very much. The assignments are a bit more practical, and require some thought while debugging. Although some TensorFlow experience from Course 2 is expected and useful, this course requires some additional reading of the TF and Keras manuals. My only suggestion to the development team would be that they improve the NST assignment's introduction of TF methods like assign() and InteractiveSession.

創建者 Selina N

2020年3月20日

It's an exciting course. I find very interesting to learn object detection, facial expression and face recognition. The concept of neural style transfer is easy to understand and funny to generate image to absorb the style from another image. The explanation is useful. One improvement is some assignments only import the trained models with extra source code. It would be better for students to build by themselves to go through the whole model development step by step.

創建者 Michael G

2021年3月19日

Some of the concepts in this course were at times hard to grasp. I'm still fuzzy around filtering and pooling concepts so will need to revisit. Andrew's lighthearted nature and good humor though; added levity to this otherwise fairly complex subject. My takeaway is that I have much more to learn about the subject. This class however has been a fantastic launchpad to an entirely new domain for me. I already bought some literature to dive deeper.

Thank you guys :)

創建者 ABIR E

2021年3月7日

Just wonderful! and especially unique! : we could never find such a deep and detailed course on computer vision and its applications.Terrific! (just for fun: before I always say : I need to go deeper (I have a gap to fill in computer vision), but now that's it: I went deeper than any "Inception..."(those who are going to take the course will understand the joke I just used (suspense: it concerns "Leonardo DiCaprio" ...), go take the course, without hesitation!

創建者 Rahul K

2018年3月6日

Very intricately explained course! Prof. Andrew has gone the extra mile here, making sure that the basics of CNNs have been imbibed thoroughly. Kudos to the programming assignments - They're undoubtedly the toughest of all the former deeplearning.ai courses. Use the discussion forums to help get subtle hints. I now feel that I can read CNN-related papers and even work on CNN applications. Plus, you learn how to implement Neural Style Transfer (DeepDream) here!

創建者 Chan-Se-Yeun

2018年5月1日

CNN is a tough topic to fully demonstrate. From my perspective, the lecturer simply offer an intuitive introduction and pick up some notable variant like ResNet, and illustrate the main ideas through delicately chosen case studies. That's somewhat "clever", I think. Maybe that's not appropriate, but I mean that it's friendly to a fresh learner but far from detailed and enlightening for an advanced learner. Anyway, I get to dive deeper into this field myself.

創建者 Ocean

2018年3月31日

As in every class taught by him, Professor Andrew Ng makes Deep Learning concepts and applications accessible. His clear explanations during the videos lead from learning the foundations to implementing modern-architecture Convolutional Neural Networks. He provides additional information about whether certain techniques are currently utilized in research and production which bring an important relevancy to the material. Thank you for offering this course.

創建者 Bernard C

2020年6月15日

Great intro to CNNs, how they work, how to use them and the types of problems they are good at solving. I'm glad Prof Andrew Ng touched on more advanced topics such as image detection, localisation and face verification/detection and how CNNs can be applied to such use-cases. The programming problems were challenging but not overwhelming, as long as one is willing to spend some time to understand the concepts presented and explained in the lectures.

創建者 Oleh.Davydiuk

2017年12月19日

Great course! Gives a great boost in understanding of deep learning usage while solving computer vision tasks. Different ConvNet architectures, their application, state of the art algorithms are explained in detail. Sometimes there were issues while solving programming assingments, specially at the last week, but I truly appreciate deeplearning.ai work that gives everyone the ability to learn about this things very effectively. So 5 for this course.