101C_W1_L1_DZ.key.pdf - 101C ADMIN STUFF 101C IMPORTANT STUFF ▸ Read the syllabus(on CCLE ▸ Office Hours Thursday 5:00-6:00pm ▸ Midterm in class

101C_W1_L1_DZ.key.pdf - 101C ADMIN STUFF 101C IMPORTANT...

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ADMIN STUFF 101C
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101C IMPORTANT STUFF Read the syllabus (on CCLE) Office Hours: Thursday 5:00-6:00pm Midterm in class: November 12 Final: TBD Send all academic questions to Piazza, not email. Feel free to answer/participate in discussions.
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PREAMBLES 101C
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101C STRATEGY VS TACTICS Strategy without tactics is the slowest route to victory. Tactics without strategy is the noise before defeat. — Sun Tzu
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101C LECTURE R CODE Please visit Clone/DL repo
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1 101C
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101C HEADS UP Advanced
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101C WHAT’S THE POINT Inference 2 views, “System”, Population “Probability space” “System”
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101C SUPERVISED VS UNSUPERVISED Data modeling can be divided into two paradigms. Supervised . Simply, we have at least one or more responses that we wish to predict from explanatory variables. Unsupervised . We do not have a response, but rather seek to find “patterns” amongst our variables. Most of ISLR, and this course, is dedicated to exploring the supervised paradigm.
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101C COST FUNCTIONS How do we assess the “quality” of our prediction? It depends. We don’t spend a great deal of time studying/considering different cost functions in 101C. Actuarial sciences. Quantitative Response, MSE, RMSE (same minimum) Example, AC “attainment”
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101C COST FUNCTIONS Very common cost function for quantitative response is the RMSE. RV version: Data version: [ ( Y ̂ Y ) 2 ] 1 n n i [ ( y i ̂ y i ) 2 ]
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101C STRATEGERY Our general business in this course, and others like it, is to create from data, . This process itself is a function . ̂ f ( x ) ( X , y )
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101C FUNCTIONS THAT CREATE FUNCTIONS For example, consider the multivariate linear solution: Notice that this itself is a function of our data, .
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  • Spring '15
  • vivianlew

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