The final data was derived by applying all the changes mentioned above it, e.g. separating into train/test set, imputing missing values etc. This is a graphical representation of what we did in this video.
Yes, understand. But considering the vastness of the subject, we thought it would be a best to focus on the slides. A cheat sheet would become too lengthy. However, we would take this as a feedback and would consider this when we are next udpating our courseware. Also, you can search in Google for cheat sheets related to Machine Learning and you would find a number of them available for free.
The slides used in the video, and the slides attached here, have discrepancies again. Some individual sldies are missing. I am not making the effort myself to show you every difference.
Please find out yourself and help in getting the exact slides described in the video, else it becomes a problem with continuity
We have created these slides keeping in mind that there is no affect on continuity, so if we have ommitted some slides it must have been done purposely. Also, I checked these slides and could not find any missing content. Having said that, I maybe wrong, and so would request you to notify us of any missing slides and we would incorporate those if necessary.
Say you want to select a subset of a population in which each member of the subset has an equal probability of being chosen, then you use Random Sampling. With compareprops, we are simply comparing the % error for overall, after random sampling, and after stratified sampling.
Please login to comment
29 Comments
This video seems to be very similar to Topic 5. Why are the topics duplicated? If they are duplicate, I can skip topic 20. Pl clarify.
Upvote ShareHi,
Instead of skipping it altogether, I would suggest you to go through the video at 2x speed.
Thanks.
Upvote ShareI did not understand at 3:04:05
What is final data ??
What are things which we are doing in final dataset??
Upvote ShareHi,
The final data was derived by applying all the changes mentioned above it, e.g. separating into train/test set, imputing missing values etc. This is a graphical representation of what we did in this video.
Thanks.
Upvote Sharewhy in this my name is not showing
Upvote ShareHi,
Please try the following command:
PS1 [\u@\h \W]\$
Thanks.
Upvote ShareIs any cheat sheet prepared?
Upvote ShareHi,
As of now we do not have any cheat sheet, but you can download the slides for your reference.
Thanks.
Upvote ShareIn video it is mentioned that you are going to do that.
Upvote ShareHi,
Yes, understand. But considering the vastness of the subject, we thought it would be a best to focus on the slides. A cheat sheet would become too lengthy. However, we would take this as a feedback and would consider this when we are next udpating our courseware. Also, you can search in Google for cheat sheets related to Machine Learning and you would find a number of them available for free.
Thanks.
Upvote ShareCan you paste some good Google links here.
Upvote ShareHi,
Please open www.google.com and search for "machine learning cheat sheets".
Thanks.
Upvote ShareIf we are considering all the attributes in the model, then why did we carry out stratified sampling only on median income attribute earlier?
Upvote ShareHi,
This is done to make the data inclusive of all categories since that is the target variable.
Thanks.
Upvote ShareHi,
Please check if you are providing the correct path for the data, and if the file is present on that path.
Thanks.
Upvote ShareWhere is the housing file. I am unable to find it
Upvote Shareplz help
Upvote ShareHi,
You need to clone our GitHub repository as shown in slide# 5 to access the housing.csv file.
Thanks.
Upvote ShareThanks Sir. I got the file. Thanks for your help.
Upvote ShareThe slides used in the video, and the slides attached here, have discrepancies again. Some individual sldies are missing. I am not making the effort myself to show you every difference.
Upvote SharePlease find out yourself and help in getting the exact slides described in the video, else it becomes a problem with continuity
Hi,
We have created these slides keeping in mind that there is no affect on continuity, so if we have ommitted some slides it must have been done purposely. Also, I checked these slides and could not find any missing content. Having said that, I maybe wrong, and so would request you to notify us of any missing slides and we would incorporate those if necessary.
Thanks.
Upvote Sharewhere is the housing.csv file ? I tried to find the path datasets/housing/ both in hadoop folder and also the linux shell, but couln'd find it
Upvote ShareI got it. Nevermind. Inore this question
Upvote Sharecbar.ax.set_yticklabels(["$%dk"%(round(v/1000)) for v in tick_values], fontsize=14)
Upvote Sharepls sir explain the role of this line
Hi,
This sets the tick values/labels for the charts.
Thanks.
-- Rajtilak Bhattacharjee
Upvote Sharehello sir , can you explain how random sampling works formula ..... i dont understand how the values comes for random sampling in compareprops
Upvote ShareHi,
Say you want to select a subset of a population in which each member of the subset has an equal probability of being chosen, then you use Random Sampling. With compareprops, we are simply comparing the % error for overall, after random sampling, and after stratified sampling.
Thanks.
-- Rajtilak Bhattacharjee
Upvote ShareHi, I am not seeing s and c parameters on pandas dataframe.plot. Can you please explain how to take it?
Upvote Share