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I know this is offtopic, but this time I have to comment the task. I am commenting the project, in case you really want to apply this for students. I think is it very dangerous to the society in general, if people that are "beginner in data science" create ML models that work on topics that are ethnical critical and highly biased, especially if ML ...


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Tru to make some features from the datetime columns - attr = ['Year', 'Month', 'Week', 'Day', 'Dayofweek', 'Is_month_end', 'Is_month_start', 'Is_quarter_end', 'Is_quarter_start', 'Is_year_end', 'Is_year_start'] you can google search about making date features. 2) Find the cumulative sum of the events - cumsum_df_all = df.groupby('column')[other-columns]....


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When I started learning about ensemble methods, this youtube video help me greatly. The idea is that you fit the model on the data, calculate the error and then work with the error. So yes you should use a weak learner to predict your data and then, use another weak learner. There are some more videos in the same channel that give a great explanation to have ...


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There are many methods to connect two different kinds of datasets Python Pandas - Merging/Joining left − A DataFrame object. right − Another DataFrame object. on − Columns (names) to join on. ... left_on − Columns from the left DataFrame to use as keys. ... right_on − Columns from the right DataFrame to use as keys. ... left_index − If True, use the index (...


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