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The best approach is to start with EDA(Exploratory Data Analysis)
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As you get the data, start with EDA (Exploratory Data Analysis). You need to understand the data and try compare with business sense (It include trend, outlier, missing values, seasonality, and lot more) PS: More you question your data, better you can do your modelling. Less
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there should have two utility functions, one for number of people received mail, one for the money spend: U1=g(X) - f(0.5X); U3=g(0.9X) - f(0.4X). if money is the most important constraint, function f would be a very steep function, thus U3 > U1; if people is the most important, g would be a very steep function, thus U1 > U3. if we have g and f defined, we can set U1=U3, Less
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I'm sorry if i understood the question wrong. But wont the option 2 better in every scenario? It costs the company 40c to send the mail with 90% accuracy. So to have the same reach to number of people as of option 1 (say we want 100 people to get the mail), we just need to send the mail to 111.11 people in option 2. With 90%, it will reach 100 people and will cost $44.44 whereas it will cost $50 with option 1. It will not matter if only the accuracy rate was 80% in option 2. Less
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The dataset should be sorted before merging.
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In the merge statement, BY variables should be provided , used in for sorting.
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I would choose work on correctly because it takes some more little time but in the end client satisfied from this work and give some more project in future so i will see company profit. Less
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i would choose work on time. because you don't want to be rushed at work or a project you're doing and could cost you or your company , on just because you rushed something you had little time to do. Less
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We're sorry you had a bad experience, whoever you are :( All our technical positions require some level of coding. We try to make this clear in the very first conversation we have with all candidates. We will take this feedback and improve from here. Thank you for sharing. Less
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depends on job to job
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There is a lot of videos on this