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學生對 提供的 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的評價和反饋

57,312 個評分
6,579 條評論


In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. 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....



Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course


Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.


5676 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 5700 個評論(共 6,507 個)

創建者 Martijn v d G


The level of detail in this course really leads to a good understanding. A bit more programming exercises with TensorFlow (more than a single model) would be good to understand the intricacies a bit better.

創建者 Armaan


Extremely well designed course, the key reason for 4 stars is Andrew Ng's amazing leactures. The programming assignment though do quite a bit of handholding which can be reduced.

Amazing experience overall!

創建者 Haiwen Z


The course is great for beginners, and I'll recommend watch the vid with Deep Learning on MIT Press. The only cons for me is that subtitle is toooo big, I wish I can change the font size on the vid setting.

創建者 Gianluca M


Very short, but very interesting. Some more advanced topics are presented that students don't typically learn on coursera courses, such as improvements to gradient descent, batch normalization, and dropout.

創建者 Philip


Good course, not quite as intuitive as the first course in the specialisation 'Neural Networks and Deep Learning' but still very good. Its also great to have some exposure to Tensorflow through the course,

創建者 Arsen K


Great course. One star was taken off, as I would like to see more in-depth info on Batch Norm and a bit more discussion on how to compute gradients in case that is used. But generally that's a minor detail

創建者 Jatin


This was a great course....but at some places I felt that the details have been hided a little....only in few videos.........but overall it was a great of the courses...I have ever seen ..

創建者 Ashwin A R


This course helped in deepening knowledge about optimization techniques and how they could make ML/DL algorithms robust while training. This also provides a good introduction to the Tensor flow framework.

創建者 Charles H


The lectures are all really good, but the programming assignments feel like they hold your hand too much. It's very easy to sort of slide through them without having a good understanding of the material.

創建者 Aditya K


Everything till now was good, But I can't tell why my forward propagation method is rejected although it matches the expected output. So my marks were deducted for it without any reasonable explanation.

創建者 Vu N M


A bit boring with this course at the first sight, but later when you work with the real system, this course can be a bible for you. The valuable experiences from Andrew Ng are shared through this course

創建者 Gillian P


Though very good, his course might be a little less polished than the previous. One more week diving into frameworks would (maybe keras to see a more functional level of Framework) would be appreciated.

創建者 Manoj A


There was no exercise on hyper-parameter tuning so the course seemed incomplete. I think week 3 should be split into 2 weeks with first week focusing on hyper-parameter tuning and second on TensorFlow.

創建者 Øystein S


Ng is an excellent teacher, and it was fun to learn about programming frameworks. However, the programming exercises are very simple, and the videos about numerics go very slow, thus 4 stars and not 5.

創建者 Benjamín V A


Very good course, useful and smart. Some of the example are on tensorflow 1 but I think that they will update them soon to keras tf2 Thank you!

I will pass on what I have learned here to undergrads :)

創建者 Yan L


very useful course, especially the last tensorflow assignment. the only reason i gave 4 stars is due to the lack of practice on batchnorm, which i believe is one of the most usefule techniques lately.

創建者 Ashim


Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

創建者 Hans J


great and practical insight. carefully crafted assignments. still coding in python and the quirks coming with it are sometimes of equal difficulty if not worse than understanding the explained theory

創建者 Kevin C


Excellent content. The grader seriously needs to be updated thogh. For example, it needs to be Python2 and Tensorflow2 compatible and also needs to be robust in handling common syntaxes such as "-=".

創建者 mitch d


Would have liked to see the math and more complete explanations for all the things that Prof. Ng glosses over by saying "you don't really need to understand XYZ". Even if this material was optional.

創建者 Ravindranadh R


Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video

創建者 Nguyễn H T


I think this course is great. Because we learn about some definitions about hyperparameters, optimization which are frequently appears in papers or in the functions in some Deep Learning frameworks.

創建者 Rajeev s


very good course with deep knowledge of each parameters. Little bit stretched at tensorflow. A bit of overview on tensorflow API and tensorflow architecture could have been better before exercises.

創建者 Sankalp B


Great teaching from Andrew Ng as always. Would've loved to learn the math behind optimization techniques, but nevertheless Andrew gave intuitions of the algorithms which cleared up a lot of stuff.

創建者 Peter F


few minor errata within the assignments that haven't appeared to be fixed even 1 year after reported. But otherwise learned a lot and enjoyed the course style and will continue to learn this spec