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.
I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
por Anurag A•
This course has been really insightful into how we should work with machine learning projects. True, that most of the ideas discussed here are not covered in normal university curriculum. Thanks a lot to Professor Ng for coming out with this really helpful course.
por AJAY G•
According to me, It is a very good course. In this course, they have taught about what can be the best practice to handles errors in the projects. They have taken different scenarios and gave us what can be the best choice that you can take to handle the problem.
por Akshat J•
Once a person has a knowledge of how to become a developer in the prevoius courses, this course gives you the knowledge to escalate from developer to a project architect. It teaches crucial techniques required to guide the training model to produce better result.
por Selim R•
I feel this is an extremely important course for all aspiring deep learning practitioners: being good is not only about knowing the algorithms and architectures, but also how to best manage your time and choose the most promising avenues to explore. A rare course
por Prakhar P•
This is an exceptional course which helps tremendously in deciding the strategy for Deep Learning projects. A course which is based on practical challenges we face during implementation of real ML problems and projects. Thank you Andrew Ng, this is very helpful.
por Fahimul H•
This was a much needed course after the 2nd one in this specialization! This course provides a clear and essential picture that is needed during development stage as well as shows the scopes of applying different techniques/blocks that were taught in course two.
por Raul T•
Shows methods for improving performance of deep learning setups in a time efficient manner. I like that deciding what to try next for improving a deep learning setup's performance is a recurring topic in Andrew Ng's courses. Knowing this can save a lot of time.
por Tolga B•
Very well structured (pun intended) and informative course! Andrew makes a fantastic job transfering his knowledge to his students. I gained very much insight in general for prioritizing different tasks in machine learning projects and planing the future steps.
por Isaiah A•
This class, although short, was very interesting and serves as a useful guide to aid in building a deep learning model from scratch. The quizzes are really interesting as well as it makes you think about a step-by-step process in your own model implementation.
por Jay G•
A fantastic course. I believe the strategies presented are practical and powerful in actually developing a deep learning system. I very much look forward to encountering those first problems and using these strategies to guide my model development. Well done!!
por Gillian P•
Great course covering topics that are not seen anywhere esle and are probably highly udnerestimated. The graded simulations are a very good idea that could be used in other courses as well. Professor Ng excellent performance is no surprise for anyone having fol
por Kyung-Hoon K•
This strategic thinking for planning ahead will absolutely save tons of times of ML developers when building a real-world ML system. This course gave me a lot of thinking points, even without programming assignment. Thanks professor Ng, Mentors, and classmates!
por Matthias T H H•
Excellent course on how to analyze errors of machine learning applications. This material provides good ways to improve the speed of iteration over any machine learning project.
This class is unique as professors rarely provide this kind of insights. Thank you!
por Nguyen M•
At first, I don't think this is a too exciting course for me. But it turns out really helpful to learn more about how to debug your ML model and make it better. It introduces many ways and approaches to debug a ML model and the solution to the problems as well
por Mahmoud H•
It is vital before diving in advanced concepts in ML or DL to learn about how to structure ML projects. This course paves the way to this fundamental hot topic. As usual, Andrew makes it easy and illuminated to clearly understand and develop your skill in DL.
por H A H•
the tips are given by Andrew Ng...that is the best for any machine learning project... I think everyone should try this course for performing better on the ML projects...once again thank u Andrew for this such a good content...highly recommended for everyone.
por HE Y•
This course has given me a systematic insight of machine learning project, which helps me to handle the machine learning problem from a global point of view. I'm eager to apply these knowledge in real machine learning project to better understand the essence.
por Balaji G•
A very much essential course for a ML team manager.. In-depth insights into the error analysis and to study the performance of the network in different perspectives. Hats-off to Prof.Andrew Ng for very nice demonstrations with lots of examples and case study.
Worth the time and effort. Although this course did not contain the programming aspects, but it was helpful nevertheless. This course actually taught me how to properly go about my machine learning project and how to troubleshoot if I encounter some problems.
por DOLA R•
This course give me direction to structure my project in better way. Content of this course was really awesome and most amazing part was the flight simulator for machine learning. Thank you Andrew Ng sir for beautifully presenting the idea, thank you so much.
por Benji T•
Short course but i think this is the most important course out of the 3 as it is more applied. Everything in this course is new to me... , had to read the discussion for help on the quiz. Hope to appreciate what i learn after i start my deep learning project!
por Vijay A•
Knowing the algorithms alone doesn't help much in developing ML applications. We should be able to tackle any problem and drive our project towards the intended goal.This course provides some handy tips and tactics for the same.Well taught as usual. Cheers!!!
This course is very useful. The 'Simulator' is very cool. After finishing the homework, I have a better understanding on how do deal with a real project. I'm trying to solve a problem in my work, I think this skills mentioned in the course will help me a lot.
por Mirza A A B•
This course was directed towards giving more of a general perspective on an ML project. Although it was a brief one, it gives enough insight to continue and develop on the concepts taught. The best part as always is the inspiring and motivational guest talk.
por Victor A M B•
Un curso corto con mucha información, pero muy muy instrucivo de cómo abordar los proyectos de deep learning o redes neuronales, se te enseña desde el análisis del error hasta la transferencia de conocimiento, lo cual es bastante interesante.