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      1 <!DOCTYPE html>
      2 <html lang="en"><head>
      3 <meta http-equiv="content-type" content="text/html; charset=UTF-8">
      4   <meta charset="UTF-8">
      5   <title>Andrew Laack</title>
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    105 
    106 <meta name="description" content="Andrew Laack's personal website showcasing research, machine learning projects, work experience, and studies in computer science. Explore code repositories, book recommendations, and find my contact information." />
    107 </head>
    108 <body>
    109 
    110 
    111 	<h1>
    112 		Andrew Laack
    113 	</h1>
    114 
    115 	<nav class="navigation">
    116 	  <a href="#research">research</a>
    117 	  <span class="separator">|</span>
    118 	  <a href="#code">code</a>
    119 	  <span class="separator">|</span>
    120 	  <a href="#studies">studies</a>
    121 	  <span class="separator">|</span>
    122 	  <a href="#blog">blog</a>
    123 	  <span class="separator">|</span>
    124 	  <a href="#contact">contact</a>
    125 	</nav>
    126 
    127 
    128   <hr>
    129   <h2 id="research">research</h2>
    130   <p> My main research interest is classical machine learning. In particular, oblique decision trees, ensemble methods, and interpretability.
    131 	
    132 <h3 id="publications">publications</h3>
    133 <ul>
    134   <li>
    135 <strong>Laack, A. D.</strong> (2025, May 8). <em>CART-ELC: Oblique decision tree induction via exhaustive search</em> [Manuscript under review]. arXiv. <a href="https://doi.org/10.48550/arxiv.2505.05402" target="">https://doi.org/10.48550/arxiv.2505.05402</a>
    136   </li>
    137 </ul>
    138 
    139 
    140   <hr>
    141   <h2 id="code">code</h2>
    142         <p>I like building software and implementing machine learning research. <a href="https://git.laack.co/andrew"> My code</a> is self hosted. I have some code available on my <a href="https://github.com/andrewlaack">Github</a>, but I am not a fan of the platform becoming the de facto standard for code distribution given its proprietary nature.
    143 
    144   <hr>
    145   <h2 id="studies">studies</h2>
    146 
    147   <p>
    148   I graduated from the University in Wisconsin-Superior with a BS in CS in the Spring of 2025. I am also starting a Master's degree program at Georgia Tech in the Fall of 2025. I have taken a fair number of computer science courses and math courses, but I have found it much more rewarding to self-study. Below is a non-comprehensive list of books I have read and recommend to those interested in machine learning.
    149   </p>
    150 
    151   <p>
    152     <h3>ml book recommendations (in order)</h3>
    153     <ol>
    154 		<li> Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Geron</li>
    155 		<li> The Elements of Statistical Learning by Hastie, Tibshirani, Friedman </li>
    156         <li> Deep Learning by Goodfellow, Bengio, and Courville</li>
    157 		<li> Reinforcement Learning by Sutton and Barto</li>
    158     </ol>
    159 
    160   </p>
    161   <p>
    162 	<h3> math book recommendations (unordered)</h3>
    163     <ol>
    164 		<li> Probability and Statistical Inference by Hogg and Tanis</li>
    165 		<li> Calculus: Early Transcendentals by Stewart </li>
    166 		<li> Linear Algebra Done Right by Axler </li>
    167 		<li> Discrete Mathematics and Its Applications by Rosen</li>
    168 		<li> Mathematics for Machine Learning by Deisenroth</li>
    169     </ol>
    170   </p>
    171 
    172 	<p>
    173 		These were the most impactful math and machine learning books that I read early on. For those interested in reading them, I would recommend first reading Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow to get a good understanding of what machine learning is all about and how to use modern machine learning tools. I would then start reading the math books to gain a strong understanding of linear algebra, probability, and calculus, prior to returning to the more theory based machine learning books. Once all of these have been read and well understood, it becomes evident what is of interest to the reader and thus their paths may diverge, but I think these recommendations are non-controversial.
    174 	</p>
    175 
    176   <hr>
    177   <h2 id="blog">blog</h2>
    178         <p>
    179 On <a href="https://blog.laack.co" target="">my blog</a> I discuss my views about software, freedom, and other topics of interest.
    180         </p>
    181 
    182   <hr>
    183   <h2 id="contact">contact</h2>
    184 
    185   <p> Email contained in metadata: </p>
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