ED
Aug 22, 2020
Excellent start for digging into topics that are not taught nowhere else. The author books 'Machine Learning Yearning' is a great next read that goes deeper in some of the aspects, really recommended.
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.
By Arun Y
•Oct 24, 2017
This course made me more skillful in deciding the factors to improve the performance of my model without wasting much time.
By Vincent L
•Aug 26, 2017
Very useful to have clear guidelines to deal with datasets, how to synthesize them eventually and clarify transfer learning
By Nnaemeka N
•Mar 22, 2023
This course has given me the tools I need and has given me the confidence I need, to take on any machine learning project.
By v n k
•Jul 30, 2021
This course gives you immense knowledge, regarding all the strategies that are required to, make a ML project successful.
By S M
•May 1, 2021
Great course! A quick way for getting direction, tips and tricks when trying to work through machine learning problems. :)
By Pratik U
•May 17, 2020
it was a great learning experience . the questions in the quiz were quite detailed and tested every aspect of our learning
By Kartikeya G
•Apr 5, 2020
This part of Deep Learning Specialisation is very helpful because this help us in resolving our problem related to dataset
By Sumedh K
•Jul 14, 2019
Amazing tips and tricks to fine tune and improve the Machine Learning models. And as always Andrew Ng does not disappoint.
By Damianos M
•Mar 11, 2019
Very interesting course!! It had many practical and important insights to deploy deep learning for real-life applications!
By alrojas68
•Nov 28, 2018
Very useful aproach to think about my next project on the ML Industry. I can see saving me a lot of time during a project.
By Yan-Jen H
•Sep 9, 2018
Great course!! Very useful tips for analyzing the model, and can find the more promising directions to optimize the model.
By Pavel K
•Mar 3, 2018
I expected more practical exercises. The "Course 3" ended up more theoretical than practical. Maybe I'll rewatch it later.
By Prasanna K
•Nov 25, 2017
Awesome course. Videos, Notes and Assignments really solves the purpose. Looking forward to do more courses from the team.
By Achen
•Oct 28, 2017
Useful_knowledege_and_rarely_taught_in_other_books/blog/college_classes_(Somehow_I_can't_type_spaces_in_this_comment_zone)
By Derek H
•Jul 18, 2020
This course has been useful for me immediately in the workplace, for getting things done and showing results for my work.
By Zobov S
•Jul 3, 2020
Also the amazing course from specialization. A tad less exciting than previous ones, but still very useful and practical.
By shubham k
•May 31, 2020
This course is excellent. It clears all the concepts from scratch. Thank you Andrew ng for giving such wonderful content.
By Ankush P
•May 29, 2020
A must-do course for anyone who is looking to participate in a competition or creation a model for real-world application
By Prosenjit C
•Sep 15, 2019
Great course, helped me to really understand the details on how a Deep Learning Project should be executed at every step.
By Abhishek B
•Sep 4, 2019
As always, great work by Andrew and team. Got to know many new concepts like Multi-task learning and end-to-end learning.
By Milos V
•Jul 30, 2019
Andrew was on the top level as usual. Just for somebody interested in more of such advice: look at his "ML Yearning" book
By punit v
•May 24, 2019
By attending these lectures years of learning which only could have possible with experience can be learned in few hours
By Jiayang T
•Apr 19, 2019
As a new grad job seeker, this class is important for my career thought it's high unlikely be asked in the job interview.
By Utkarsh G
•Dec 19, 2018
In this course, you will get the knowledge that no one teaches you, that is how to make models in the most efficient way.
By arslan s
•Jul 8, 2018
It is a bit theoretical, but it is very helpful for those guys who are planning to start their setup of Machine Learning.