DG
Apr 14, 2023
Extremely educational with great examples. Helpful to know Python beforehand or the syntax will become a time sync, and understanding the mathematics as going through the class makes it a decent pace.
SL
Aug 27, 2022
After copleting the course I found all conceptual knowlegde for visualising and implementing the algorithm in my work. Before this course I was not using the full potential of the advanced algorithm
By khawaja s
•Oct 3, 2023
thnks
By DEMAH A S A
•Sep 13, 2023
greet
By Muhammad S S
•Sep 7, 2023
Great
By Seyyed M M
•Jun 3, 2023
Good!
By Putu G P A
•Apr 7, 2023
Great
By Yu-Cheng C
•Nov 5, 2022
Nice!
By Piyush J
•Oct 7, 2022
none
By Ahmed N
•Nov 16, 2023
Good
By chadia e k
•Nov 11, 2023
nice
By Dini P U
•Oct 14, 2023
good
By Rizki A
•Oct 12, 2023
good
By Trisno P R
•Oct 8, 2023
Joss
By Haveela D
•Sep 19, 2023
good
By Chonchal k
•Sep 14, 2023
good
By Angger M R
•Apr 5, 2023
good
By Fitrah S
•Mar 23, 2023
cool
By Ande R
•Feb 17, 2023
Good
By Lovish C
•Feb 4, 2023
nice
By Marlon S V L
•Jan 15, 2023
Good
By Arkadiusz J
•Mar 5, 2024
:)
By Jaber
•Sep 3, 2022
<3
By Bhavesh P
•Jul 9, 2023
By Serge B
•Nov 30, 2022
.
By Will S
•Jan 3, 2023
Really good conceptual teaching of ANNs and decision trees, but it's a little lacking in the Python implementation. It teaches you how to program an ANN with any number of layers/neurons, but there is no mention of finding the "optimal" number of each. The last week on decision trees and ensemble models feels rushed as there is only one lab and required assignment, so it completely misses the Python implementation of XGBoost. However, it teaches the essential functions in each library, so one can easily continue his or her learning with Kaggle competitions and Stack Overflow. In the end, it's meant to introduce working professionals to the most common ML models in the world today, and it does that very well, but not much more.
By Britto T
•Jan 6, 2024
This course is brilliance personified especially the intuition (which is the primary focus). The reason for a 4-star rating is, that it ended quickly, and it does not cover the codes in detail, but rather the logic on 'why we do what we do'. Andrew Ng drips knowledge and passion . I only wish he formulates a course named "AI-Scientist" with a one year completion time, that covers topics right from basics of Python, basic math, advanced math, ML, DL, NLP, MLOPs through and through. I am excited to jump into my next course :) Thank you Andrew Ng :)