MG
Mar 30, 2020
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.
AM
Nov 22, 2017
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.
By Kranti A
•Mar 8, 2018
Very well structured course, understands better and improving my skills much more further in this course. Learning a lot.
By Ayush T
•Feb 3, 2018
It's a another great course from the deeplearning.ai. This course is really helpful in managing my deep learning project.
By Shivam K
•Sep 5, 2017
Awesome insights to starting and structuring a deep learning problem. Must see for even experienced people in this field.
By Guru P B
•Mar 25, 2021
got very fruitful knowledge about how to structure ML projects but still 'how to structure experiments' part is missing.
By Rishikesh B
•Sep 8, 2020
Really helpful Course in being able to decide parameters around my on-going College Project on Food Calorie Estimation..
By Krishnan R
•Aug 28, 2020
Very good case studies in-line with concepts taught in the course. Very good Extract of real life project experience .
By Shankar P
•Aug 22, 2020
Prof. Andrew Ng is so awesome, so much useful to strengthen foundations and first principles along with solid intutions.
By Nikhil R
•Jun 12, 2020
This is a great way to learn to make choices for solving machine learning problems. Should have more quizzes like these.
By Lim Z Y
•Jun 10, 2020
Its a good course to build the basic knowledge what you should have before starting the implementation of deep learning.
By Vitor A
•Apr 22, 2020
Very explanation of training sets, dev sets, test set. How to create strategy for creating a Machine Learning algorithm.
By zheng
•Feb 14, 2020
Great course! I learned a lot of best practice on how to structure a ML project, from metric defining to error analysis.
By Hector L
•Jan 21, 2020
This was a short course, but it was packed with first-hand knowledge of the industry. I enjoyed the quizzes/simulations!
By Jenny C
•Jan 1, 2020
The speed of a couple of video's (e.g. End-to-end deep learning) seems to be accelerated, which appears a bit unnatural.
By Stefan S
•Dec 27, 2019
Very good complement to the first two courses on deep learning, a lot of useful tipps on machine learning understanding.
By Karthikeyan T P
•Dec 4, 2019
Highly recommended. Gives deeper insights into how a real-time project would be like and how to deal with the situation.
By Namburi S
•Nov 19, 2019
It helped me a lot to understand the subtleties related to data structuring before even worrying about the architecture.
By yesid a c m
•Nov 3, 2019
Muy bueno, pero podrÃan profundizar un poco más en los comentarios que hacen en cada pregunta después de ser calificada.
By Karan S
•Sep 2, 2019
One of my best experiences every with DeepLearning. The quiz questions helped a lot to understand real world challenges.
By Harish J
•Jul 20, 2019
Professor Ng gave a very good explanation on how to approach ML projects step-by-step. The quizzes are also really good.
By Jakub V
•Sep 23, 2018
Lot's of practical advice. Revising the questions / answers in the quizes could potentially further improve the quality.
By Matt C
•Nov 25, 2017
another excellent series of information about deep learning. The entire course has been great and I recommend it to all!
By Haedar h
•Feb 26, 2024
It's just great to learn from someone like andrew, he gives you a great intuition about all the concepts in this field.
By Abhijeet N
•Apr 9, 2023
It helped me develop my intuition skills when faced with the real world ML related problems still waiting to be solved.
By G H K
•Oct 19, 2022
I was able to finish it faster than normal. This was very practical and relatable for me because of my job experience.
By Manuel J C S
•Dec 30, 2021
Pretty good course, it can show you how to make some decisions that you probably faced before and took the wrong ones.