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on 17-Feb-2026 (Tue)

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Flashcard 7799290334476

Tags
#RNN #ariadne #behaviour #consumer #deep-learning #priority #recurrent-neural-networks #retail #simulation #synthetic-data
Question
A [...] is a well-defined visit of a consumer to a web-shop: a subsequence of events within the consumer’s history that lay no further apart than a predefined time difference
Answer
session

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

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A session is a well-defined visit of a consumer to a web-shop: a subsequence of events within the consumer’s history that lay no further apart than a predefined time difference

Original toplevel document (pdf)

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Flashcard 7799292169484

Tags
#causal #inference
Question

The G-methods family, as developed by James Robins and colleagues, specifically includes:

  1. Inverse probability weighting (IPW)
  2. G-computation
  3. [...] of structural nested models
Answer
G-estimation

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The G-methods family, as developed by James Robins and colleagues, specifically includes: Inverse probability weighting (IPW) G-computation G-estimation of structural nested models

Original toplevel document

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The G-methods family, as developed by James Robins and colleagues, specifically includes: Inverse probability weighting (IPW) G-computation G-estimation of structural nested models Inverse probability matching (propensity score matching) is not technically a G-method. While it shares the fundamental goal of addressing confounding and selection bias, it employs a d







Flashcard 7799294266636

Tags
#Linux
Question

How to delete all files before a certain date in Linux

find . -type f -mtime +XXX -maxdepth 1 -exec rm {} \;

The syntax of this is as follows.

-mtime +XXX – replace XXX with the number of days you want to go back. for example, if you put -mtime +5, it will delete everything [...] then 5 days.

Answer
OLDER

statusnot learnedmeasured difficulty37% [default]last interval [days]               
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scheduled repetition interval               last repetition or drill

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-maxdepth 1 -exec rm {} \; The syntax of this is as follows. -mtime +XXX – replace XXX with the number of days you want to go back. for example, if you put -mtime +5, it will delete everything <span>OLDER then 5 days. <span>

Original toplevel document

How to delete all files before a certain date in Linux
How to delete all files before a certain date in Linux Posted on: September 15, 2015 If you have a list of files, but you only want to delete files older the a certain date, for example, a maildir folder with 5 years worth of email, and you want to delete everything older then 2 years, then run the following command. find . -type f -mtime +XXX -maxdepth 1 -exec rm {} \; The syntax of this is as follows. find – the command that finds the files . – the dot signifies the current folder. You can change this to something like /home/someuser/mail/somedomain/someemail/cur or whatever path you need -type f – this means only files. Do not look at or delete folders -mtime +XXX – replace XXX with the number of days you want to go back. for example, if you put -mtime +5, it will delete everything OLDER then 5 days. -maxdepth 1 – this means it will not go into sub folders of the working directory -exec rm {} \; – this deletes any files that match the previous settings.







Flashcard 7799296625932

Tags
#feature-engineering #lstm #recurrent-neural-networks #rnn
Question
retailers observe the [...] data from a panel of customers and use the history of customers' browsing behavior to make predictions about browsing behaviors, purchasing propensities, or consumer interest
Answer
clickstream

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

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retailers observe the clickstream data from a panel of customers and use the history of customers' browsing behavior to make predictions about browsing behaviors, purchasing propensities, or consumer interest </s

Original toplevel document (pdf)

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