Very practical advice for a beginning deep learning engineer on what to do to avoid getting lost in the hyperspace of all the parameters one could change to train a better neural network model. I do wish however there was more explanation of why the different heuristics work, that Prof. Andrew suggests.

Good practical tips for planning out your machine learning projects. Every machine learning engineer should check out this course as it will be really helpful in planning your machine learning projects and allocating time for tasks in the project. And as usual, great, lucid instruction by Andrew Sir! :)

Very interesting to see a transversal course of how to model and manage ML and DL projects, I am happy to learn new tricks to deal with train/dev/test sets with different distributions, dealing with small datasets and new techniques to apply transfer learning and lastly, how multi-task work in general

Great course by Prof Ng. I had taken his Machine Learning course a few years ago, so expected high standards of content and assignment preparation - I was not disappointed. Staff is very responsive and helpful in forums as well. I highly recommend it. Taken as part of the DeepLearning specialization.

Amazing course where Andrew NG shares his advice on how to work with datasets of different distributions etc. Coming from such an experienced practitioner is so helpful.

The Quizes are really helpful as they deal with case study and really make you feel like you're in the spotlight

Loved this course!!!

The two quizzes of this course were unique. Never came upon such a quiz in any other online course. Along with the videos and supplementary pdfs, this course was quite unique and important in every aspect. I will use the approach I learnt here on my next ML projects. Thanks to Andrew Ng and the team.

Really good course. As a machine learning practicioner I discover new ways to attack a machine learning problem. It taught me where should I focus to achive my goals faster. I think that in the exams they could give a little more explanation of why some answer is wrong. Overall an excellent course.

Very good course. Professor Ng explains very well why some strategies are better than others and how a deep learning practitioner or team can save a huge amount of working hours by following the instructions taught in this course. There are also useful, in-depth discussions in the forum. Thank you!

Great practical insights of how to start a ML project, how to improve/optimize the system, how to identify and troubleshoot common problems in deep learning. The course provides comprehensive high level guidelines for anyone who uses machine learning, even without having any programming experience!

The course has practical content. When took in the Deep Learning Specialization I noticed that some parts of the material were already known from previous courses. Indeed, in previuos courses the repeated aspectes are presented from a different angle, but probably there is an area for limiting it.

It's like understanding deep learning: a team leader's perspective. Andrew may be the first instructor to give this kind of course. Based on his experience in building practical and large scale machine learning system in Google and Baidu, the course content is highly inspiring and worth listening.

As an Ops person by nature, i like to see methodology and structure along with systematic approaches to results - be they solutions or problem solving. This course adds to that area, by providing best practices and ideas, it forms the basis from which these challenges can be addressed. Very good.

THE must have course for every machine learning enthusiast!! The course is very enjoyable with invaluable insights and expertise from a well-rounded deep learning practitioner. It greatly helps to clear the machine learning workflow and best practices to quickly develop, iterate and ship a model.

This course had no programming assignments. Yet I found it amazing. It truly gives you insight into how to engineer your projects to account for real world conditions.

Liked the flight simulator analogy to this course. Accelerated learning is really the great benefit of following Andrew's advice.

I've done a Master degree in IA and the things covered in this course have never been addressed by any of my professors. Now I've been working in a Machine Learning team for the past two years now, and I believed these lessons would have been of great value, and would have saved me a lot of time!

I Thought I knew every thing from what I've learned in previous courses but in this one, I do learned a lot more and even some of questions which didn't strike into my mind and I think they are questions I would be faced in the future, were answered here. thank you for this comprehensive course.

This a great course on Deep Learning, the contents are so full of interesting information, actually, this course could also be called "Everything you wanted to know about Deep Learning (but were afraid to ask)".

As always, Andrew delivers a great course, whose content is ready to put in practice.

This course is very helpful to learn best-practices and problem-solving strategies that can help improve our deep learning algorithms. While I think the ultimate way of learning is through practice, here you can at least get a list of things to try in the future as you work on these algorithms.

Although this was a bit hard for me to understand but still through the quizzes i got an insight so as to where will these advice be applicable and where i can use what i studied.

I am thankful to the teachers and a especial thanks to Coursera for giving me the opportunity to avail this course.

I think this part of the specialization is a great value key, and makes the difference with other courses, self learning books, etc. The contents of this individual course helps a lot into understand and improve knowledge studied in previous and next courses. I definitely recommend this course.

A very unique course. It's like having a casual conversation at Andrew Ng's office, where random bits and pieces of industry knowledge comes up. Though the field is rapidly evolving and some of the "best practices" keep changing, the underlying philosophies still make this a worthwhile course.

This is the one that talks a lot about how to struture DL projects. And many methods have been taught in this course including focusing on the error control, transfer learning, multi-task learning. After learning these methods, tuning a DL project or starting a DL project will be a lot easier.

The content, examples, assignments, and quizzes are thoroughly developed. All the courses of the specialization share the same notation and lead a student from basic concepts to complex ones helping to develop an intuition on each step. The best course on topic of Deep Learning one could find.

This is a unique course that provides invaluable perspective on how to direct a deep learning project. Its value is derived from understanding the performance metrics ( the data about the data) and acting in a data driven way. Anyone in charge of a deep learning project should take this class.

This is really a greate course taking ont into the deep thoughts of how to structure deep learning projects. I teaches use how to analysis the various errors like human/bayes level error, training error, traing-dev error, dev error & test error, I learnt to anaylise errors and take decisions.