OD
May 30, 2020
Amazing course. For a beginner like me, it was a shot in the arm. Excellent presentation very lively and engaging. Hope to see the instructor soon in a another course. Thanks so much. I learned a lot.
PT
Dec 1, 2018
This is an awesome module. It will open up so much inside story of ML process which is core of the topic with such a simplicity. It greatly increases my interest into this topic and this course :)
创建者 Breght V B
•May 22, 2018
Using hash function doesn't seem a good way to split the dataset:
-You could discard a relevant feature
-You will group data on a similar characteristic, which might not represent the population well
-You don't have control over the size of your split since the feature will not likely be uniformly distributed
Can't we add an index feature/column and do a modulo on the index?
创建者 Tomomasa T
•Sep 23, 2018
In The last lab, teacher says that there is 100,000 in data set , then we extract 10,000 from data set.
But there is 1,000,000,000( I checked by
'''SELECT
COUNT(vendor_id)
FROM
`nyc-tlc.yellow.trips`'''9
SELECT
COUNT(vendor_id)
FROM
`nyc-tlc.yellow.trips)
In that context, I think MOD(...) meaning is totally different ?
创建者 Anubhav S
•Jul 27, 2019
I feel that the flight and taxi cost estimation was kinda rushed. It was hard for me to follow. Ii having less knowledge about SQL was finding it to be tough. Before that, everything was clean and awesome. I think I have to revisit these courses after learning SQL better.
创建者 Venkata S S G
•Aug 10, 2019
good course. but it is just like an intro regarding how to use google cloud platform. but theory part was decent. can give it a try. but lectures were really indulging
创建者 Matthew R
•Nov 14, 2018
Some good material here, but at times it feels like an ad for GCP. And the labs are not very inventive. You just run a python notebook with canned stuff in them.
创建者 Anand H
•Oct 7, 2018
While the concepts covered were good and very valuable, I didn't like the lab sessions. Just having to walk through code is not a good way to get hands-on.
创建者 José C L A
•Apr 18, 2020
Too much content for just one week. Exercises solved and not made for students to resolve them. Suggesting more complicated tasks is not teaching.
创建者 Anupam S
•Nov 29, 2019
I could only sustain it because I have completed basic ML courses earlier. Too many tech concepts & jargons overloaded in a very short time.
创建者 David N
•Jun 14, 2019
Learning the approach was very valuable. The exercises were just copy and paste of a bunch of code that it isn't expect we understand.
创建者 Nour L
•Aug 29, 2018
It felt too hard. I liked because it gives a very good idea but the concept was too hard especially with the math involved
创建者 Cooper C
•Jan 15, 2020
This course is just ok. It is not interactive and I don't feel that I learned much when compared with other ML courses.
创建者 Nils W
•Sep 28, 2019
The course is good, but I missed the hands on part. You really do not need to code. That should be changed.
创建者 Pravin A J D
•Jan 5, 2019
not enough practical content such as types of machine learning and different algorithms to be used etc
创建者 Srinivasan D
•Jul 27, 2020
In the labs, I kept getting disconnected from the Jupyter notebooks, and had to keep reloading them.
创建者 Jon B
•Jun 11, 2018
Course includes good presentation material which unfortunately is not available to download.
创建者 Aseem B
•Aug 23, 2018
If you already know ML there isn't much in this course that will be value addition for you.
创建者 Fabrizio F
•Jul 29, 2018
The course is very well explained, but I was already aware of most subjects.
创建者 Kevin C
•Jul 15, 2018
There is a little more content here than in the 1st course.
创建者 Prateek D
•Aug 11, 2018
Please add more content, don't make it just intro types
创建者 Manuele I
•Apr 29, 2020
Talked too much...more practical example step by step
创建者 Shawn W
•Sep 19, 2019
A bit difficult when introducing the ML history
创建者 vishnu p T
•May 23, 2020
quiet difficult to undertand
创建者 Saurav K
•Jul 21, 2019
It's not much helpful
创建者 Vinit K
•Jan 22, 2019
Very Basic again
创建者 KimNamho
•Apr 12, 2019
thank you