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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


Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.


5751 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 5775 個評論(共 6,429 個)

創建者 Dinh T T


It's a wonderful course because it provides me how to improve deep neural networks and delve to some techniques to gain good hyperparameters

創建者 John S T L


Would have given 5 stars if the Jupyter exercise did not give me too much of a hard time looking for errors in syntax. Overall, great lesson!

創建者 Parag P


Loved the easy to understand explanation given by Prof. Andrew Ng for some of the most complex concepts in Deep Learning like Regularisation.

創建者 Daehee K


This class is very helpful for understanding parameters of ML except week 3 class and assignment for Tensorflow which is not fully explained.

創建者 Xiaochao G


I don't understand tensorflow mechanism and when to use what function. Should I stop to learn more tf or just move on the following courses

創建者 Nataliia K


Quite ok, but programming assignment was mostly copy-paste style. I am not able to repeat something similar independently after the course

創建者 Maximilian B


A lot of great concepts covered in the lectures but only few were explored in the assignments. The assignments seemed fairly simple to me.

創建者 Vanja T


There were grading results that seemed wrong - I've submitted report on grading to explain details. Other than that, the course was great!

創建者 Batuhan A


This course was nice for me.First Andrew Ng talks about mathematicall background of the concepts then you get hands on coding experience.

創建者 Aditya S


Good course. However expected some more mathematical proofs for some of the ideas like bias correction and exponential weighted averages.

創建者 Prerna D


Very good course. All the concepts explained very well. I just feel programming assignments were too easy, they could be a little tougher

創建者 Mohamed M A M


It's really great Mr/Andrew has a good way of explaining stuff even tho i need to search some stuff on youtube for greater understanding

創建者 2445_Nupur S


I loved the course, as it provided concise explanations and covered all important topics required in Deep Learning. Thank you Andrew Ng!

創建者 dspguy


Would have been 5 star but I found typos in the assignments and exercises -which have still not been corrected which is quite surprising

創建者 Varunraju V


Its good hands-on course but to master it will certainly requires to dwell more into the specifics and need to work on various projects

創建者 samarth


Was a great course. Learnt conceptually and implemented Momentum,ADAM & rmsprop. Wish there were more exercises to explore TensorFlow .

創建者 Benjamin J


I would have liked more programming exercises related to regularization and hyperparameter tuning, but TensorFlow was well introduced.

創建者 Paulo M


I liked the course. I just think there should be more assignments. Perhaps after each week because the content is dense and complex.

創建者 Vighnesh N G


Too much spoon feeding in the programming exercises, could have asked us to make a model with atleast x accuracy then left us alone.

創建者 Mahesh S P


This was the toughest course since lot of mathematical, especially statistics back ground is required. However, I could complete it.

創建者 Sri K


Its require basic python programming for implementation of neural networks , different models techniques to get perspective of it .

創建者 Ahmed N


One of my best courses i have ever participated in, i gained a lot of knowledge and knew the underlying mathematics of every model.

創建者 Mathieu J


Second step of the specialization,

a bit less rewarding than the fist course as more fine tuning and less overview of deep learning

創建者 Muiz V


Programming assignments could have been more challenging. Otherwise, the course instructor is pretty awesome!! Thank you Andrew Ng.

創建者 Swann C


Good material and definitely essential in order to gain a lot of time aiming at the right direction navigating all these parameters