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返回到 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

56,647 個評分
6,498 條評論


This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....



I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation


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


5651 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 5675 個評論(共 6,430 個)

創建者 Dany J


Good covering of many implementation aspects of neural networks. I find the practical exercises to lean on the tedious side while not bringing a tremendous amount of learning themselves.

創建者 Jose L M


It was somewhat frustrating to spend so much time coding raw python, just to discover that TF can do all of that with one-liners. Nevertheless it was valuable to learn the nitty-gritty.

創建者 Aditya L


Some extra information on various optimization algorithms will be good. Moreover, if there are links to some of the research papers and resources to dive into, it will help out a lot.

創建者 Tilman H


Excellent course, but I did not learn many new things (some just from a different angle). Maybe the course description should be updated to be more specific about the target audience.

創建者 Thomas D


Some very interesting material for beginners. At times it feels like concepts are being repeated over and over again, but there is enough new concepts to keep it worthwhile to repeat.

創建者 Wahyu G


Not so much different with the materials in the Machine Learning course from Prof. Andrew Ng itself. If you don't have the time to finish the ML course, then you should take this one.

創建者 Md. A J


The mathematical explanations were very good. But the coding task is always left to do at once. If it can be set after the corresponding videos as a module it would be great I think.

創建者 Alejandro N


It is an excellent course. The only weird thing it is that it uses Tensorflow 1 instead of 2. I get it why is it done, but perhaps it would have been more useful to keep using numpy.

創建者 Jorge L M B


Awesome material, and everything is well explained. I would've liked that the programming exercises were a little more challenging, though going through the code shines a nice light.

創建者 Vishnupriya V


As always Andrew Ng's clearly explains all the concepts along with practical programs. I would strongly recommend doing this course for a good solid understanding of neural networks.

創建者 Ivan


While video lectures are very well explain subject matter, practical assignments are pretty frustrating since most of the time you will be battling jupyter notebook and auto grader.

創建者 Alejandro E


Very good course, although it'd be awesome if Andrew went over the backprop associated with Batch Normalization and perhaps a programming example of using Batch norm on my test set.

創建者 Emre E


I loved the course but the tensorflow implementation was a bit weak, it passed in just 15 min video. I recommend this course but as i told before tensorflow migration is a problem.

創建者 Jeroen V


The graded functions could be a bit more free form, forcing you to think more about it. I sometimes feel that I'm more solving the "template", than I am thinking about neural nets.

創建者 Tibor S


Personally, I would like to have more programming exercises on the things that are taught (Hyperparameter tuning, Regularization) in order to compare how different techniques work.

創建者 Andrew R


Just enough explanation of material to get started on using DNNs for my own tasks. Assignments are easy, though provide good explanation of what is occurring in each line of code.

創建者 Ugo N


It's okay. It's get a bit hairy with all the notation and varied intuition, but it follows suit and is not impossible to understand! Thank you Dr. Ng, I look forward to more.


創建者 Luisa F V C


You learn about improving your capacity in the modeling and logic in your neural networks. This course is full of tips and tricks very important in your career in deep learning.

創建者 Hind A b


explained very well, interesting and engaging assignments, sometimes I get lost with all the mathematical representation and details but overall very good course I recommend it.

創建者 Mustafa S Ç


Everything was great. Every peace of information scratch in my mine. I learned a lots from course.

In the last part; Tensorflow has dramaticly changed but content didn't renewed.

創建者 Pavel B


everything you need to do is given in form of the hint. That was a nice course in terms of the explanations, but too easy in terms of applying it in a programming assignments.

創建者 Carlos M


Great for the most part, but the TensorFlow assignments felt flat and "incomplete." I ended up using Hands-On Machine Learning with Scikit-Learn & Tensorflow to bridge the gap.

創建者 Scott V


There were a few errors in the final assignment and grading is very slow. That being said, the course was informative and provided some additional "tools" to add to my toolbox.

創建者 Rocco I


Good course, as the previous ones. I wish we had the possibility to download the slides or get some summary notes... Going back to the videos to check some infos is not handy.

創建者 John O


A solid Part 2 to the deep learning sequence. My only issue here is that the final exercise emphasizes TensorFlow 1.0, which felt a little funny since TF 2 works differently.