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 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.