deeplearning.ai의 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 학습자 리뷰 및 피드백

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.

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.

It is really helpful to NN rookies like me. I have learnt a lot of important concepts and skills, such as hyperparameters tuning and variables initialization. More importantly, I gain some basic knowledge about Tensorflow, which is a widely used NN framework. I really appreciate the step-by-step instructions in the notebook assignments.

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.

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.

This is a best serie I've ever seen on digital courses overall, the sequence os topics are well planned and applied, the level is perfectly balanced to be challenger and also understandble. Contrags to professor Andrew and all his team for more on great resource to spread AI knowledge and make it accessible to most interested people.

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!!

This is great course if you have taken NN network and deep learning course to sharpen knowledge about dl optimization algorithm. Teaching was good and clear. However i think the video duration is quite long, at least it can be made under 10 minutes. Give a thumb to this course and it also introduce tensorflow to program the algorithm

highly illuminating. Finally, with this second course, I could grab the deep concepts and consequences 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.

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.

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.

Thank you so much Coursera for providing me such a good course. It was a great learning experience. The assignments and quizzes played an important role in improving my skills and giving me the confidence to implement deep NNs. I'll definitely recommend this course to others. Looking forward in doing more courses in deeplearning.ai

This is an wonderful course for people who want to learn about the ways to improve their models and make their best and more robust. Andrew Sir makes the math behind the scenes very easy to understand. The course is easy to follow as it gradually moves from the basics to more advanced topics, building gradually. Highly recommended.

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.

As usual Andrew ng Course is Awesome.

A bit of more video expatiation is needed for Tensorflow.

Labs are really helpful.

It would be grateful if they had provided notes after each lesson like in the first course(probably 1st I guess) of Andrew ng Machine Learning .

That's it, overall it is really good and useful .Thank you Andrew Sir

Andrew NG is such a fantastic teacher especially in this online mode. He provides crystal clear explanations and examples to understand why the methods work. As a learner I was only expecting to learn how to apply this to solve real problems and not to learn theoretical subtities, this is probably the best course in deep learning.

Excellent course over all, but what I like the most is how the complex math behind all these techniques are carefully hid and instead, we're given an intuition about how these techniques work. Of course, for a deeper understanding much more mathematics is needed, but they make sure that everyone has an idea about why things work.

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.

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!

Improving DL Networks in fact improved my understanding of hyperparameter tuning, regularization and optimization. The quizzes helped me getting clarity and the assignment of tensor flow gave a good introduction using functions in the tensor flow. I really enjoy learning from Andrew and look forward deep diving farther into DL.

After learning the basic knowledge of the first course, this course deepened my understanding of deep learning, and explained how to optimize the model of deep learning from the perspectives of hyperparameter tuning, regularization and normalization, and finally provided the basic knowledge of the framework based on TensorFlow.

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.

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.

One of the rare courses teaching about structured hyperparameter tuning. All the subject matter are well taught and the flow of the module is very easy to follow and understand. Together with the programming assignments, I was able to quickly grab the essentials. I highly recommend this course for any deep learning enthusiast.

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!