I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.
por Sujay K•
The course would have been more interesting if we had some programming assignments. Hands on experience into some of these cases really help.
por Daniel M•
Unique course in the sense that teaches important topics that are rarely seen in the literature and are fundamental in designing AI projects.
por Hagay G•
Had some pretty great info for junior Project Managers, for some reason, it's also hiding some extremely important info about end-to-end DL.
por Mohamed M H M A•
Some of the videos weren't of good quality. Also, I was expecting doing a real project not to make decisions based on different scenarios.
por Nikolai K•
Good course overall, would have liked to have the in-depth programming assignments though, those really made the other courses stand out.
por Shashank S S•
Learned various ways to structure ML projects in industry.
It would have been great to have few programming assignments included as well.
por Leonid M•
Some tips are very useful for practitioners but the same information is repeated over and over again that makes the course quite boring.
por aman a c•
A small course with very effective tips and tricks to figure out how to start and proceed further while building a project effectively.
I think this lecture is very useful when we make our own ML system.
Also, it has many examples about errors we can usually meet in real.
por Tim S•
Useful, practical material. I probably underappreciate the importance of someone (especially of Dr. Ng's stature) covering this for us.
por Bill T•
Very practical lessons in this module that should make you and your team more efficient in implementing deep learning on real problems.
por Edward M•
another great Andrew Ng course. This one gives practical insights in how to go about making your deep neural networks perform better.
por Mohammad H•
I really found the pilot training quizzes are great and very helpful, but some questions one can debate if has the right answer or not
Quizzes could be refined since some of the questions are really confusing & need weird pre-requisite knowledge about human physiology.
por Ioannis K•
It was an interesting course for sure, but it was a bit stretched and the notions explained could be compressed in a much shorter one.
por John E M•
I appreciate the review and hints on structuring ML projects. Just seemed a little lacking on the meat and potatoes of real practice.
por Saurabh D•
Now I know what is Machine learning and its parts eg deep learning. The curse cleared the basic structure for machine learning to me.
por JEREMY S•
Interesting to understand how to manage a problem during a ML project, really good trick and tip! Thanks Andrew and deep learning.ai!
por Alhasan A•
It would be more useful to give explanation why an answer is correct and others are wrong, such details enhance our learning so much.
por aditya g•
Machine Learning Simulator & course contents well prepares you to how a machine learning project should be structured and approached
por Huang C H•
Probably the least exciting of the five. This is a short course on how to approach machine learning projects, as the title suggests.
por Priyanka T•
I thought this course was great content wise, but needs to improve on the errata in the content (repeated video sections), and quiz.
por Bingnan L•
I think it should be useful but since I haven't got many practical experience, the course seems a little bit hard to catch up with.
por Zheng Z•
I think a little bit more programming homework can help me better understand the concepts, but other than that everything is good.
por Giovanni C•
It's a good course to gain an initial understanding on the role that different real-world considerations play in Deep Learning NN.