thanks for the great work. There is so much to learn and I appreciate the effort you made to break things down and providing lab while making the hard decisions on what to commit.
This course is so really good to learn about the general knowledge and skill of Data Science like optimization batch or regularization and so on with Google Cloud Platform.
By Somaiya J G•
By Gustavo M•
By Phạm V T•
By Manish K•
By MOHD N B A L•
By Dr. P S J•
By Balasubramanian T K•
By AMARTHALURU N K•
By Mirza s N•
By Fathima j•
By Bielushkin M•
By Atichat P•
By Fuat A•
Google provided with me an opportunity to take the specialization for free. Many thanks.
Just a comment: Labs were great. But, it takes long when i needed to start a lab, i.e. Opening a Google account every time and starting a vm. So, it would be great if i could use the same vm for more than one lab assignment.
By Carlos V•
Excellent Course, in the Art and Science of Machine Learning, I quite enjoyed the Hyperparameter tuning in the Cloud and all the advanced tips to improve the models performance, thanks Coursera and Google
By Robert L•
Sufficient theory to understand the basis of the ML approach with practical insights to help get started with building models
By Vishal K•
Nice course however I think it suits folks who have good exposure of ML to take complete advantage of the techniques
The course is difficult. You may need to review some sections because off the amount of information.
By Manish G•
The course is quite good and have balance of theory and labs. It is useful course for beginners.
By Phac L T•
It would be nice to have more complex datasets where predictions would be more meaningful.
By Oleg O•
Very good course, but probably requires some more hand-on practice
By Joel M•
good lessons and in depth coverage of a range of issues
By HUGO H•
Good course, pragmatic and full of practical exercises
By Attila B•
Really good course with a lot of practical examples.
By Pratik S•
complete hyper parameters is given in lab
By Ruslan A•
Many notebooks contain some typo/erros.