As someone new to machine learning, I really appreciate how you guys break down complex concepts with relatable real-life examples. It's been incredibly helpful! Great stuff
Useful tutorial for work with some of the basics of data cleanup, and instructive because of the problem with the exploration. I believe the goal is to predict late arrivals and their cause. At16:06 she’s working on cleaning up missing values, looking at ‘ARRIVAL_DELAY’ and the delay cause columns, while discussing the ‘CANCELLED’ column. No recognition that cancelled flights don’t arrive, as they never take place! Obviously, the columns having to do with arrival delay will be empty. All the cancelled flights should have been removed in the previous data prep section. Instructive, as it shows the importance of data prep for machine learning.
Thank you for the tutorial.I got the flights dataset from Kaggle,but the data set does not appear to have many of the columns that you have ,for example cancellation reason etc
Only after I stuck a piece of duct tape on my screen to cover this beautiful creature I was able to finally concentrate on the learning materials. Such a distraction!
previously I just watched #1 and now I'm on this session, I'm a completely newbie.. I've just set up my AI envronments(VS code,Jupter notebook,Miniconda,Pandas etc) but I don't understand.. where has she got the data? How do I know all these codes she feeds on a jupter notebook and see all data? it feel kinda advance stage all of a sudden? my challenge is how do i get to know all these codes she types just to get Jupter understand what she real wants? where can I have exercises just to sharpen my skills..Thanks.
for some reason i got boolean instead of number with the get_dummies, i fix it just adding dtype=int parameter in the function, just if someone else got the same problem
Thanks for efforts both of you - really I like it - I download the big file since I did not find diect link to the flights_sample.csv file - any how it working fine -thanks
It does not read the csv file: I get a syntax error. (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape Where do you put the csv file? How do I set the path?
As someone new to machine learning, I really appreciate how you guys break down complex concepts with relatable real-life examples. It's been incredibly helpful!
Great stuff
🎉 Same thoughts, I was too tensed
Thanks to this video, now I understand
This is probably the best video I've seen on Pandas so far
Useful tutorial for work with some of the basics of data cleanup, and instructive because of the problem with the exploration.
I believe the goal is to predict late arrivals and their cause. At16:06 she’s working on cleaning up missing values, looking at ‘ARRIVAL_DELAY’ and the delay cause columns, while discussing the ‘CANCELLED’ column. No recognition that cancelled flights don’t arrive, as they never take place! Obviously, the columns having to do with arrival delay will be empty.
All the cancelled flights should have been removed in the previous data prep section. Instructive, as it shows the importance of data prep for machine learning.
Nicely put together 👏, both of you guys are awesome, and to those of your colleagues who help you be awesome
Thank you so much 😁
Great Effort. Kudos to both of you
Thanks!
I love your accent and the quality of your English!
Thank you! 😃
Very nice course. Thank you for sharing your knowledges!
Glad it was helpful!
Are there any challenges like this, where people are asked to take a dataset and find patterns like this I wonder. Great job!
Very good course! Thank you very much!
You're very welcome :)
Great introduction to pandas!
Thank you for the tutorial.I got the flights dataset from Kaggle,but the data set does not appear to have many of the columns that you have ,for example cancellation reason etc
hi i keep getting file error when I run the code to read the csv file for flights at the part of your tutorial in 4:51
Only after I stuck a piece of duct tape on my screen to cover this beautiful creature I was able to finally concentrate on the learning materials. Such a distraction!
🤣🤣🤣🤣
ooow you have a soothing voice, I'm just saying...nways the lessons so informative.
Hello @Misra, for the One Hot Encoding is it better to use the Pandas function or the Sklearn?
quick question: can i clean the data with SQL or EXCEL and then import the cleaned CSV dataset in order to build the model?
How did you take the sample of the original dataset?
why you didn't cast y_flights values to numeric as well?
in minutes 12:44 you forgot to mention that we have to import matplotlib
from matplotlib import pyplot as plt to display hist
Good catch
previously I just watched #1 and now I'm on this session, I'm a completely newbie.. I've just set up my AI envronments(VS code,Jupter notebook,Miniconda,Pandas etc) but I don't understand.. where has she got the data? How do I know all these codes she feeds on a jupter notebook and see all data? it feel kinda advance stage all of a sudden? my challenge is how do i get to know all these codes she types just to get Jupter understand what she real wants? where can I have exercises just to sharpen my skills..Thanks.
Cok iyi, tesekkurler!
good work ,keep go ,ty
Previously arrival delay was not there greater than 15 later on it is there like greater than 1500 can u explain it please.
for some reason i got boolean instead of number with the get_dummies, i fix it just adding dtype=int parameter in the function, just if someone else got the same problem
For me to receive the boolean value I use X_flights = X_flights.astype(int)
Add this line of code
Thanks for efforts both of you - really I like it - I download the big file since I did not find diect link to the flights_sample.csv file - any how it working fine -thanks
Great!
It does not read the csv file: I get a syntax error.
(unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape
Where do you put the csv file?
How do I set the path?
you have to escape the backslash by using another backslash (C:\\Downloads\\flights.csv), or use forward slashes.
Thank you!
well done
Thank you!
Great
Thanks!
Tyty. Did not catch her name?
You're very welcome! It's Mısra.
Great
Thanks!