学生对 DeepLearning.AI 提供的 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的评价和反馈
课程概述
热门审阅
DD
Mar 28, 2020
I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.
AM
Oct 8, 2019
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
776 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 800 个评论(共 7,283 个)
创建者 Kai C
•Nov 3, 2017
Through this course, I learnt how to tune hyperparameters and a set of optimization for the train process of neural networks. Further I got the opportunity to play TensorFlow. I really enjoy it.
创建者 Sudipto C
•Sep 14, 2017
Well structured course and very good material. Thoroughly enjoyed Prof. Andrew Ng's lectures and leart a lot from them. I only wish the programming assignments were a bit tougher than they are.
创建者 Alexander G
•Sep 3, 2017
Thank you for your explanation that are very useful and clear! You present so much difficult material but you do it very concentrate. Thank you for practice and excercises that are very helpful!
创建者 Mike D
•Aug 22, 2021
Great course, recommended. Coming from a corporate coder/admin/architect/data engineer background this specialization is making me think and work, just as I hoped. Thanks Dr. Ng and everyone.
创建者 Susan M
•Apr 14, 2021
For a first time learner in this arena, this was a great intro to what and how to proceed. I could take the course a few more times to be ready to use this in industry. Excellent instruction.
创建者 Stanislav T
•Jul 14, 2018
This course contains great hints for optimisation and tuning. Even if you know about neural networks this course can still be valuable to fill in some gaps and help you improve your algorithms.
创建者 Tannmay Y
•Jun 4, 2018
Really Amazing course! Highly recommended for all those who wants to go deep in deep learning and understand important methods and logics behind them. Programming assignments are very good too.
创建者 Gadepalli A ( A S
•Mar 14, 2018
One of the best courses in its class, Prof.Andrew Ng has made it absolutely simple, yet, thorough. The assignments are focused and quickly take one through the crux of what is actually needed.
创建者 Mingzhu D
•Sep 27, 2017
It is a great course, continuing with the first deep learning course. It is mainly about how to optimize for better results. And the programming assignments are down-to-earth and help me a lot.
创建者 Fuyang L
•Sep 23, 2017
Andrew Ng is so good at making things easy to understand and he gives you the most essential things you need to know in order to carry out real world machine learning tasks. Highly recommend :D
创建者 Alister M
•Aug 24, 2021
I learned a lot about setting up neural networks and what to expect when setting them up. Finally I understood the importance of using Tensorflow and other environments like it moving forward.
创建者 gravitycuda
•Feb 19, 2019
A must have course to know the effect of Hyperparameter tuning, and a great programming exercise on Tensorflow for Beginner. I highly recommend this course if you want to build accurate models
创建者 Darshil P
•Nov 7, 2018
Amazing course, well structured. Learned a lot about tuning parameters and different optimisation algorithms. Looking forward to complete specialization. Thank you Coursera and Andrew Ng Sir.
创建者 Bernard W
•Aug 18, 2018
Concise and comprehensible. A lot of ground is covered, but I found by taking notes by hand and replaying key parts of lectures, I was able to follow along and understand the course material.
创建者 Shrey P
•Jun 13, 2018
Good course. Teaches you the practical aspects of deep learning. Take everything with a grain of salt. As Dr Ng has pointed out, deep learning knowledge of domain seldom translates to another.
创建者 Linghao L
•Jan 1, 2018
Comprehensive course on deep neural net optimization skills, you will get a pretty complete understanding of how to make your nets work more efficiently and save a lot of time. Don't miss it !
创建者 Shaoduo X
•Sep 10, 2017
The last part of the tensorflow tutorial (model() function) might need more explanation on the some tensorflow internal stuff: like I have a question, how does TF store the optimal parameters?
创建者 Li P Z
•Oct 7, 2019
fantastic course, although programming assignments not as challenging as Andrew Ng's Machine Learning course, inviting experts like Yoshua Bengio to give insights is also uniquely valuable...
创建者 CHEYU L
•Jul 13, 2019
This course is really helpful for improving the structure of the nn model. The most important thing is that now I have some direction to keep learning and getting my algorithm better. Thanks~
Loved everything, great course, i would have liked a bit more detail on tensor flow, but i know Prof. Ng has taken out a tensor flow course now, i plan on taking that too. Thank you Everyone!
创建者 Alfonsus G C
•Nov 8, 2018
Great course for early machine learners to gather intuition and knowledge about how the code in deep learning frameworks actually do at the lower-level, but some typos still need to be solved
创建者 Jie Y
•Dec 26, 2017
Interesting content, feel like building the deep learning/neural network bigger and more complex. Very good course series. Definitely recommend to my friends who are interested in this field.
创建者 Zacchaeus W
•Aug 20, 2017
Perfect Course! Perfect Intuition! Perfect Practical Learning! MUST TAKE!!!!
P.S: become more familiar with numpy before taking this course. Otherwise, you may not understand some of the code.
创建者 Vincent Z
•Apr 5, 2020
This course is quite helpful for me. It covers the fundamentals of neural network and tensorflow. It teaches knowledge of neural network in a systematic way and I have learned a lot from it.
创建者 Abhishek K G
•Oct 18, 2019
The course was very good to make understand the hyperparameters in the neural network and how to optimize them to produce good accuracy over the model. I have learned a lot from this course.