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

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

4.9
57,409 個評分
6,595 條評論

課程概述

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....

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AM
2019年10月8日

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

XG
2017年10月30日

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.

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5726 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 5750 個評論(共 6,521 個)

創建者 Miroslav A

2019年1月27日

Excellent lectures, well prepared, very good examples, great teacher.

I would happily give it 5 stars, if not the constant issues with Coursera infrastructure, crashing notebooks/kernels.

創建者 Anthony K

2018年11月8日

The course is very interesting and fairly well laid out but some simple typos can cause some confusion and they have been there for a long time based on some info in the discussion forums

創建者 Sandeep P

2018年6月24日

Nice course. Great introduction to hyper parameters in neural networks and also nice assignment on tensorflow. It would have been even better if they introduced tensorflow in more detail!

創建者 ZW

2018年9月2日

Good material and some very nice practical tips. A few typos here and there in the course material made it difficult at times to debug the code, which is the reason for docking one star.

創建者 Dany J

2017年11月10日

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

2018年9月14日

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 Akhtar H

2021年1月21日

Nice explanation of Tensor flow. Hyperparameter tuning was explained in easy and robust way. Programming Assignment is tricky but forum comments helped a lot in resolving the problem.

創建者 Aditya L

2020年8月8日

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

2020年5月10日

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

2019年7月7日

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

2018年3月10日

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

2020年9月29日

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

2020年9月8日

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

2020年6月24日

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

2019年6月22日

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

2019年3月14日

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

2018年2月19日

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

2020年10月9日

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

2018年11月14日

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

2018年8月6日

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

2018年4月20日

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

2017年10月10日

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.

Ugo

創建者 Luisa F V C

2020年8月5日

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

2020年3月5日

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

2019年10月22日

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.