Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization に戻る

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42,366件の評価

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4,520件のレビュー

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....

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.

Jan 14, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

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by Eulier A G M

•Aug 31, 2019

The course is very well structured, most of the topics here is perhaps kind of boring due the lack of real-problems projects, but if you stick to it and learn the concepts, will boost your understanding when using Deep Neural Network Frameworks, such as Tensorflow. That makes creating DNN easy to set, understand and apply to your problems.

by Suhas P

•Sep 21, 2017

Introduction to TensorFlow was wonderful. This course has helped me visualize and experience end to end flow of an actual machine learning project that helped a lot. Thanks to Andrew for taking efforts to design the course in a user friendly way. Programming tips are intuitive, helps save your time and allows you to focus more on learning.

by Chandan N

•Nov 27, 2019

Great insights into the theory of regularization and famous optimization algorithms like RMSProp and Adam. Helps in developing intuition regarding these algorithms work and implementing them from scratch was pretty rewarding as well.

As usual, Prof Andrew Ng patiently explains the theory and helps in building understanding of the material.

by Saransh M

•Aug 20, 2019

Started from the basics but made sure that they provided an in depth understanding of some very important concepts like hyperparameters and regularization will well structured quizzes and interesting programming assignments. Really liked the course and would suggest it to anyone trying to set their feet in the field of ML or Deep Learning

by Shuvayan G D

•Jun 16, 2019

This is probably one of the best courses on hyperparameter tuning. Along with Andrew's teaching , the course assignments are just perfect to get the perfect intuition of how optimizers work in the deep learning frameworks , also you will be able to build your own optimizer from scratch after doing this course , though not recommended. : P

by MOHD F

•May 17, 2019

This is an amazing course, it helps me a lot to gain the basic intuition, and the idea behind tunning our model, this course provides understanding basic maths of how we can knob various hyperparameters, which would eventually lead us to a better statistical model in term of both speed and performance... Thankyou coursera ...Thanks Andrew

by Ivan T

•Feb 04, 2018

Another great course! Enjoyed it very much. Learned a lot of useful techniques. One thing that could be nice to do is to add references and optional material for students who want to go deeper (i.e. add references to publications related to some technique or a blog page). Looking forward to taking more courses in the Deep Learning series!

by Jonah N

•Jun 04, 2018

The course really gave me insight into some of the optimization methods that are commonly used. It also helped me to get a better understanding of Tensorflow. I think y'all have done a good job presenting the information with just the right amount of math and explanation. I have recommended this course series to multiple friends already.

by Arpit B

•Sep 11, 2017

Thanks Andrew, As always you have been a superb teacher, I am very happy with the content of the course.

One suggestion is to increase the level of difficulty in assignments. Or you can have one more course to develop an difficult deep learning application from scratch, through which we can all apply the concepts and tricks you explained.

by Yan

•Apr 13, 2019

Although the concepts of deep learning ( ie. the gradient descent, the chain rule ) are quite easy-understanding and clear to most people, how to choose the hyperparameter and how to effectively carry out the projects are real essence. That's what I learn from this course. Thanks for so many genius researchers contributing to this area.

by Jayant R

•Feb 24, 2019

I didn't knew much about different optimization algorithms and how they work. This course helped in understanding those concepts. Also leaened how to tune hyperparameters. Now, I am able to read tensorflow codes on net and also able to write basic code. Prof. Andrew Ng is the best. Concepts gets very clear on first time watching video.

by Edwin G

•Dec 12, 2017

Some of the coding at the end was pretty tricky and I had to use the forums for help. That's what they're there for of course but I don't think the introduction to Tensorflow syntax was really sufficient - or maybe there could be some more optional help or resource to look through to help. Still very interesting and rewarding course!!

by Virginia A

•Jan 07, 2020

highly illuminating. Finally, with this second course, I could grab the deep concepts and conseguences of many terms I heard so many times during talks between data scientists. I feel now I could easily use what learnt to participate actively to those meetings and practically try things out on my methods and make them perform better.

by Karan S

•Apr 27, 2019

I'd been working on Neural network Models in my undergrad projects, but really couldn't answer much of the problems that I faced. The title isn't too appealing, because no new Network Architectures are taught, but in my opinion, this course is on par with the previous course on building Deep Networks from scratch. Highly Recommended.

by Anand K M

•Feb 10, 2018

A very nice course providing intuitions and concepts for tuning the hyper parameters in a neural network.

Also, provides a taste of using Tensor Flow (Neural Network Framework) in a comprehensive manner.

I would give my deepest thanks to the instructor, Prof. Andrew Ng for his invaluable time for building the course for the learners.

by Tanveer M

•Aug 28, 2019

Professor Ng's very clearly put a lot of thought into breaking down deep learning into the most understandable way for students around the world and it shows through the quality of this course. I cannot recommend this course enough to anybody who is looking to do machine learning, or simply understand the process from a high level.

by Bernard O

•Oct 24, 2018

The tips and great guidelines one gets from this course are gems in their own right. Practitioners in particular will get to appreciate all the usable advice to improve their neural networks and at the same time get to understand the principles behind the scenes on what truly drives those optimizations. Highly recommended course.

by Sinkovics K

•Aug 15, 2018

The course material is detailed and comprehensive and presented in a very digestible way. I felt like the home works lack a few topics (e.g. learning rate decay implementation, which I would find to be a useful exercise), but they give you a good understanding of what is going on. All in all, I definitely recommend this course!

by 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.

by 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.

by 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!

by 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.

by 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.

by 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

by 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!