Awesome tutorial. The concept is intuitivo, running a query usong previous result, as chaining. In the example given, it is clear how you get the aggregate min and max of all data set by collapsing the table. Well done
You explain complex things in very easy way. I appriciate your effort. You were setting self assessment questions, but unfortunately I did not find any link downloading the Dataset and without that it was impossible practicing on your self test questions rather than just watching the video.
Thanks! ✌️ Not a schema per se, but many database info is available in SQL Workbench under the *Database Explorer* menu. Sample data, table structure, CREATE TABLE command, etc, etc. everything you need
Good question, from that result, you compute the percentage. The answer to your question is pivoting ( columns to rows) . Reshaping, long to wide. It is a good use case of cte With cte_reshaping as ( The result of this query Select count(*) as count, is_it_late) Select sum(case when is_it_late = 'late' then count end ) as late, Repeat for other two categories (Early and ontime) From cte_reshaping Hoping this helps
Hello Tomi, Is it recommend to code all the machine learning algorithms from scratch so that I can learn math behind it or just understand and start to code?
Yeah, it makes sense... I mean definitely not all of them, but you can go ahead and try the simpler ones (and validation methods, too). That will give a solid understanding of the basics. Then later on, when you get more advanced, you can just dig deeper into the specific model that you'll use for your given project. Then most probably it won't be necessary to code it from scratch to understand it well enough to apply it correctly. Smart question, btw.
Awesome tutorial. The concept is intuitivo, running a query usong previous result, as chaining. In the example given, it is clear how you get the aggregate min and max of all data set by collapsing the table. Well done
Very well Explained ....Thanks you
Waiting for your next two videos! Really helpful!
Very soon!
Very well explained... Thanks again!
Much needed concepts. Super.
Thanks! : )
Great content Explained very wel........Thank you.........
You explain complex things in very easy way. I appriciate your effort. You were setting self assessment questions, but unfortunately I did not find any link downloading the Dataset and without that it was impossible practicing on your self test questions rather than just watching the video.
Tons of thanks brother! Can I get flights table dataset?
Great video. Would be great if you had a diagram of the database schema with all the tables with their rows and columns.
Thanks! ✌️
Not a schema per se, but many database info is available in SQL Workbench under the *Database Explorer* menu. Sample data, table structure, CREATE TABLE command, etc, etc. everything you need
Hi Tomi,
I loved your SQL playlist. Can you make a playlist too on Python for Data Science?
Thanks -- yes, I've already started to draft it. I'm not sure when I'll record it but hopefully in the near future.
Did anyone tell you that look very similar to Paul Rudd? Btw great video and explanation of concepts
Yes, I'm Ant-man (as a side gig).
Thanks, btw!
Thank You Very Much :)
Where can the dataset be accessed to enable me to practice your question
i am using google cloud how can i get the table you are working with so i can practice
Do you have anything on Machine Learning in say, MATLAB?
Hello, is it possible to group many rows into one output row? example, print 'early', 'late' and 'ontime' on one output row.
Good question, from that result, you compute the percentage.
The answer to your question is pivoting ( columns to rows) . Reshaping, long to wide. It is a good use case of cte
With cte_reshaping as (
The result of this query
Select count(*) as count, is_it_late)
Select sum(case when is_it_late = 'late' then count end ) as late,
Repeat for other two categories (Early and ontime)
From cte_reshaping
Hoping this helps
Where can I get the data for This tutorial?
Hello Tomi,
Is it recommend to code all the machine learning algorithms from scratch so that I can learn math behind it or just understand and start to code?
Yeah, it makes sense... I mean definitely not all of them, but you can go ahead and try the simpler ones (and validation methods, too). That will give a solid understanding of the basics.
Then later on, when you get more advanced, you can just dig deeper into the specific model that you'll use for your given project. Then most probably it won't be necessary to code it from scratch to understand it well enough to apply it correctly.
Smart question, btw.
i think problem number 1 can be solved easily by just write *Limit 1* at the bottom of your query.
Very well Explained ....Thanks you