Intro_Data_Science_Fall_2018/lec3.html at master · lydiahsu/Intro_Data_Science_Fall_2018 · GitHub

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<!DOCTYPE html>
<html lang="en-us">
  <head>
    <meta charset="UTF-8">
    <title>Lecture 3</title>
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    <style type="text/css"> <!-- .tab { margin-left: 40px; } --> </style>
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  <body>
    <section class="page-header">
      <h1 class="project-name">Introduction to Data Science</h1>
      <h2 class="project-tagline">Columbia University Science Honor Program Fall 2018</h2>
    </section>
    <section class="main-content">
<h3>

<p , style="color:black;"> <b> 1. Probability Review</b> </p>
  <p class="tab", style="color:black;"> - Slides: <a href="reading/prob_tutorial.pdf"> view </a> </p>

<p , style="color:black;"> <b> 2. Intro to R and RStudio</b> </p>
  <p class="tab", style="color:black;"> - Slides: <a href="reading/Lec_2.pdf"> 1 </a>
                                                <a href="reading/Lec_2_1.pdf"> 2 </a>
                                                <a href="reading/Lec_3.pdf"> 3 </a> </p>

<p , style="color:black;"> <b> 3. Optimality of Bayes Classifier</b> </p>
  <p class="tab", style="color:black;"> - Reading: <a href="reading/optimality.pdf"> view </a>

<p , style="color:black;"> <b> 4. Classifiers: Naive Bayes/ LDA; QDA/ Logistic Regression/ Support Vector Machine </b> </p>
  <p class="tab", style="color:black;"> - Slides: <a href="reading/SVM.pdf"> view </a>

<p , style="color:black;"> <b> 5. Coding: Multiple Classifier </b> </p>
  <p class="tab", style="color:black;"> - Background: <a href="reading/Introduction to the Sloan Digital Sky Surveys.pdf"> view </a>
  <p class="tab", style="color:black;"> - Data: <a href="data/Skyserver_SQL2_27_2018 6_51_39 PM.csv"> download</a> </p>
  <p class="tab", style="color:black;"> - Code: <a href="example/Classifiers.R"> download</a> </p>

    </section>

  </body>
</html>