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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
43,181 個評分
4,645 條評論

課程概述

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....

熱門審閱

AM

Oct 09, 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

XG

Oct 31, 2017

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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176 - Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的 200 個評論(共 4,573 個)

創建者 Kazi M R

Jun 06, 2018

From this course I have learnt several important hyper parameters, regularisation and optimization of deep neural network. Most importantly I got my first hand-on experience on Tensorflow framework by which creating deep net modes are quite easy if someone knows the elements of a deep net. I wish I will proceed for next course.

創建者 Ian C

Oct 01, 2017

Learning about TensorFlow is brilliant. It's very hard to get a good understanding of what goes on in TensorFlow without fully understanding the neural network coding setup. This course beautifully combines the two. There were some minor frustrations with the final TensorFlow programming exercise, but overall this is excellent.

創建者 Jeroen M

Jan 10, 2018

Great course, a few rough edges in the exercises and I also feel the exercise comments give away a bit too much (would be better if the student needed to figure out things by himself a little more). But these are minor details, I've learned a great deal in an amazingly short span of time, from one of the top minds in AI today!

創建者 Jeff R

Oct 02, 2017

I appreciate the large amount of time that has gone into preparing this course. I note that there are a large number of corrections in the errata forum that have not been reviewed by staff. In particular there are some obvious errors in the programming assignments that could easily be corrected with a small investment in time.

創建者 Murat T

Dec 24, 2018

Topics cut in to sections are well defined and so clear. Programming assignments definitely gives you hands on experience. Also, math is demystified that you track with high school math. If you used framework like Keras and you want to know why and when you need to use that function,parameter etc., you would love this course.

創建者 Gilles D

Sep 06, 2017

Eventually a clear and definitive explanation about Network initialization, regularization and optimization. Good insight share on hyper-parameters prioritization.

We learn the how and why and suddenly, it all becomes a little bit less mysterious. It is all clearly explained in a very accessible way.

Great value for my needs

創建者 Xuefeng P

Aug 29, 2017

This course really gives you a fundamental and practical ideas about the hyper-parameters of DNN, and the way of tuning them. The part I liked most is the last programming assignment ---- play with Tensorflow!!! The assignment walks you through Tensorflow structure and basics in a very organized fashion.

Highly recommended!

創建者 Mihai L

Jan 21, 2018

This course is also interesting. The art of tuning hyper parameters and other optimization techniques are very interesting and nicely explained.

The introduction to Tensorflow and assignment is also interesting.Overall the difficulty is not high but the concepts are really powerful and important ,most scaffollding is done

創建者 Vlad M

Sep 07, 2018

The course part is overall good.

The last assignment can be improved in two key ways:

The comment # Z3 = np.dot(W3,Z2) + b3 should be # Z3 = np.dot(W3,A2) + b3 - figured this out by myself without help from forums. :)

Also, the Adam optimization is not very apparent in the instructions - searched in the forums for issues.

創建者 Brad M

Aug 22, 2019

In my deep learning classes in academia, hyperparameter tuning was always "hand-waved" away - my questions were always deflected, or put off. This class answered every one of my questions, and made me more confident I'd be able to implement a DL system in industry, and be satisfied with the results. Very good course!

創建者 Toby K

Nov 01, 2019

I am working through the DL specialisation. Consistently good teaching style and the programming assignments are suitably pitched for getting the learner to pick up methods quickly e.g. Tensorflow syntax for self-application later. Good course and looking forward to the next in the series. Well done Andrew and team.

創建者 Ankur T

Nov 21, 2018

word is not sufficient signup and experience it. For a deep learning beginner who already have math background can easily understand concept behind it but for implementation you need to refer extra materials on internet and book too. Andrew Ng explain only concept and recipe but for practice you will struggle hard.

創建者 afshin m

Feb 05, 2018

This course is continuation and a requirement of the first course. Really like the learning style of how first course and the first 2 weeks of the second course taught neural networks by doing all the math and calculations manually and finally introduced Tensorflow with parallels of what was taught in the class.

創建者 arulvenugopal

Dec 17, 2017

This is another excellent course in this specialization. I enjoyed the programming assignments. The instructions, tips made Tensor flow coding section to be easy . However, few blocks consumed more than few hours, due to placeholders. logic and the TF documentation is overwhelming. I am proceeding to next course.

創建者 Wei L

Aug 26, 2017

This course is harder than the previous one. It teaches more details of tuning parameters and optimization in deep learning. In the end it also teaches tensorflow which is really helpful. It's like a programming course, nerally all the commands have been already provided, so it's not hard to get the code correct.

創建者 姜云鹏

Nov 21, 2017

It is really good and teach me the basic understanding of DeepLearning back propagation and gradients optimization like Momentum, RMPS, Adam finally I learn how to use Tensorflow to train my model.

But there are some mistakes in the assignments and also in the grade so that it costs me a lot of time but useless.

創建者 Vinodh R

Nov 12, 2017

The course content was excellent. The only issue is that there were some glitches with the grading of the second week programming assignment, in that I could obtain the expected output, but with repeated submissions, there would be (different) sections which could not be graded due to unnamed technical issues.

創建者 Renato L

Jul 03, 2019

Excellent content and very well explained. Thanks for this amazing course.

The course cover the building blocks of a Neural network. Andrew (and his team) did a great job by organizing the content in an evolving way in which you have the chance to build the knowledge from each piece of a (deep) Neural Network.

創建者 Bryan H

May 28, 2018

Practical programming lessons, and well-paced enjoyable lectures.

Comments:

Move tutorials on TensorFlow to Course 3, which was the most obscure part of the course. TensorFlow isn't as intuitive as other numerical toolboxes, so spending more time on the foundations of TensorFlow might reduce the learning curve.

創建者 Mojtaba H

Feb 11, 2020

It covers very good tips and tricks to build and enhance deep learning model.

Andrew is the best teacher for ML and Deep Learning, he covers all theory and practice simultaneously.

In this course you can understand all mathematical intuitions and implementation of neural network from scratch by your own codes.

創建者 Rob v P

Oct 02, 2017

This second course in the specialization is really great. I have gained a lot of insight in hyperparameter tuning and the reason why they work (or don't ;-). It is much easier now to understand what models are doing and why we need certain techniques. This is again one of the best courses for deep learning.

創建者 Abdallah D

Feb 03, 2020

Fantastic course providing a broad overview of hyperparameter tuning in deep neural networks. The introduction on TensorFlow is informative. Looking forward to the three remaining courses of this great specialization on machine leaning. Thanks Andrew and their assistants for putting those courses together!

創建者 Daniel R B

Jun 06, 2018

I really liked the course. The forum is very helpful navigating programming errors during the assignments.

A thing to improve would be to get the feedback from the forums to the lectures. Specially in corrections that should be made to the programming assignments that don't match the expected result. Thanks

創建者 Steve S

Dec 11, 2017

Provided a lot of deeper insights passed over in the previous course in the specialization. Between this course and the previous course, you feel like you have a very solid beginner's understanding of deep learning, but one that is also practical enough and comprehensive enough to start coding on your own.

創建者 Marcin G

Oct 15, 2017

Andrew Ng is a great teacher and will get you excited about improving deep networks. In this course you will get to know how to increase performance of your network. Essential course for deep networks specialists and amateurs. Additionally you will get to know most influential people befind the technology.