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<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
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<h2 class="text-center">aggregate</h2> | ||
<div class="panel panel-default"> | ||
<div class="panel-heading">aggregate</div> | ||
<div class="panel-body"> | ||
<p>aggregate: summarize the data in a certain way.</p> | ||
<p>SYNTAX: collection.aggregate([list of parameters])</p> | ||
<p>each parameter maps a function, e.g, $group, to the arguments of that functions.</p> | ||
<p>Functions include: | ||
<ul>$match: filter document</ul> | ||
<ul>$group: group documents</ul> | ||
<ul>$project: which fields to show in the end result</ul> | ||
<ul>$lookup: combine documents from different collections</ul> | ||
</p> | ||
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<head> | ||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script> | ||
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<h2 class="text-center">join</h2> | ||
<div class="panel panel-default"> | ||
<div class="panel-heading">join</div> | ||
<div class="panel-body"> | ||
<p>embedding: document containing other documents</p> | ||
<p>referencing: refer to other documents</p> | ||
<p>join: combine information from different documents</p> | ||
<p>single source of truth: all information is stored in one place only</p> | ||
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<head> | ||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script> | ||
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<h2 class="text-center">schema</h2> | ||
<div class="panel panel-default"> | ||
<div class="panel-heading">schema</div> | ||
<div class="panel-body"> | ||
<p>schema: validator for adding documents to collection</p> | ||
<p>SYNTAX: same as with querying the collection.</p> | ||
<p>You can also add the validator such that any added document is checked</p> | ||
<p>db.command("collMod", "COLLECTION", validator=SCHEMA)</p> | ||
<p>It is more common to use JSON schema, which allows for a more detailed error message.</p> | ||
<p><a href="https://json-schema.org/" target="_blank">json schema</a></p> | ||
<p>In Python, this works via "import jsonschema"</p> | ||
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<!DOCTYPE html> | ||
<html lang="en"> | ||
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<head> | ||
<title>Algoritmiek cheat sheet</title> | ||
<meta charset="utf-8"> | ||
<meta name="viewport" content="width=device-width, initial-scale=1"> | ||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script> | ||
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<div class="row"> | ||
<div class="col-md-6"> | ||
<div class="panel panel-primary"> | ||
<div class="panel-heading"> | ||
<h3 class="panel-title">Key concepts</h3> | ||
<span class="pull-right clickable"><i class="glyphicon glyphicon-chevron-up"></i></span> | ||
</div> | ||
<div class="panel-body"> | ||
<p><a href="algoritmiek/intractable.html" target="_blank">intractable problem</a></p> | ||
<p><a href="algoritmiek/polynomial.html" target="_blank">polynominal</a></p> | ||
<p><a href="algoritmiek/p_vs_np.html" target="_blank">P vs NP</a></p> | ||
<p><a href="algoritmiek/pspace.html" target="_blank">PSPACE-complete problems</a></p> | ||
<p><a href="algoritmiek/big_o_notation.html" target="_blank">Big O Notation</a></p> | ||
<p><a href="algoritmiek/greedy.html" target="_blank">greedy</a></p> | ||
<p><a href="algoritmiek/dynamic_programming.html" target="_blank">dynamic programming</a></p> | ||
<p><a href="algoritmiek/efficiency.html" target="_blank">efficiency</a></p> | ||
<p><a href="algoritmiek/asymptotic.html" target="_blank">asymptotic</a></p> | ||
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<h3 class="panel-title">Graph</h3> | ||
<span class="pull-right clickable"><i class="glyphicon glyphicon-chevron-up"></i></span> | ||
</div> | ||
<div class="panel-body"> | ||
<p><a href="algoritmiek/bipartite.html" target="_blank">bipartite graph</a></p> | ||
<p><a href="algoritmiek/independent.html" target="_blank">independent</a></p> | ||
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<h3 class="panel-title">Predict</h3> | ||
<span class="pull-right clickable"><i class="glyphicon glyphicon-chevron-up"></i></span> | ||
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<h3 class="panel-title">Evaluate</h3> | ||
<span class="pull-right clickable"><i class="glyphicon glyphicon-chevron-up"></i></span> | ||
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<div class="panel-heading"> | ||
<h3 class="panel-title">Models</h3> | ||
<span class="pull-right clickable"><i class="glyphicon glyphicon-chevron-up"></i></span> | ||
</div> | ||
<div class="panel-body"> | ||
</div> | ||
</div> | ||
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<div class="col-md-6"> | ||
<div class="panel panel-success"> | ||
<div class="panel-heading"> | ||
<h3 class="panel-title">Programming</h3> | ||
<span class="pull-right clickable"><i class="glyphicon glyphicon-chevron-up"></i></span> | ||
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<div class="panel-body"> | ||
</div> | ||
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$(document).on('click', '.panel-heading span.clickable', function (e) { | ||
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if (!$this.hasClass('panel-collapsed')) { | ||
$this.parents('.panel').find('.panel-body').slideUp(); | ||
$this.addClass('panel-collapsed'); | ||
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<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script> | ||
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<h2 class="text-center">Asymptotic</h2> | ||
<div class="panel panel-default"> | ||
<div class="panel-heading">Information</div> | ||
<div class="panel-body"> | ||
<p>asymptotic: approaching but never connecting with a line or a curve.</p> | ||
<p>useful because we want to know how algorithms behave when n is very large.</p> | ||
<p>the definition for function that does the work: T(n).</p> | ||
<p>we have to determine the bounds of the output of T(n) for all possible values of n.</p> | ||
<p>complexity order: | ||
<ul> | ||
<li>O(1)</li> | ||
<li>O(log(n))</li> | ||
<li>O(n)</li> | ||
<li>O(n*log(n))</li> | ||
<li>O(n^2)</li> | ||
<li>O(n^3)</li> | ||
<li>....</li> | ||
<li><a href="https://www.bigocheatsheet.com/" target="_blank">bigocheatsheet.com</a></li> | ||
</ul> | ||
</p> | ||
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<div class="panel-heading">Big-O: upper-bound</div> | ||
<div class="panel-body"> | ||
<p>Big-O is used for the upper-bound of T(n).</p> | ||
<p>This is for the worst case.</p> | ||
<p></p> | ||
<p>$$ {T(n) \text{ is } O( f(n))}$$</p> | ||
<p>$$ {\text{ iff } T(n) \gt c* f(n)} $$</p> | ||
<p>$$ {\text{ for all } n>= n_{0}} $$</p> | ||
<p></p> | ||
<p>T(n) can be upper-bounded using f(n).</p> | ||
<p>T(n) is the function that does the actual work.</p> | ||
<p>O means that we upper-bound it.</p> | ||
<p>f(n) is the function used for bounding.</p> | ||
<p>The iff explains when the function can be used for upper-bounding.</p> | ||
<p>$$ {n_{0}} $$ is when n=0.</p> | ||
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<div class="panel-heading">$$ {\Omega} $$: lower-bound.</div> | ||
<div class="panel-body"> | ||
<p>Lower-bound is for the best case.</p> | ||
<p>In this case, all values must be below the value of T(n).</p> | ||
</div> | ||
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<div class="panel panel-default"> | ||
<div class="panel-heading">tight-bound</div> | ||
<div class="panel-body"> | ||
<p>You want to upper-bound a function as tightly as possible.</p> | ||
<p>loose upper-bound: an upper-bound that is correct, but far away from the actual upper-bound.</p> | ||
<p>tight upper-bound: an upper-bound that is correct and is close to the actual upper-bound.</p> | ||
</div> | ||
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<div class="panel panel-default"> | ||
<div class="panel-heading">$$ {\Theta}: exact bound $$</div> | ||
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<p>where the upper-bound and the lower-bound come together.</p> | ||
<p>there is no little theta since theta is a perfect bound.</p> | ||
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<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
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<h2 class="text-center">Big O Notation</h2> | ||
<div class="panel panel-default"> | ||
<div class="panel-heading">Information</div> | ||
<div class="panel-body"> | ||
<p><a href="https://medium.com/karuna-sehgal/a-simplified-explanation-of-the-big-o-notation-82523585e835" target="_blank">medium.com</a></p> | ||
<p>Big O Notation is the language we use to describe the complexity of an algorithm.</p> | ||
<p>With Big O Notation, we express the runtime in terms of how quickly it grows relative to the input as the input gets larger.</p> | ||
<p>Some examples of Big O Notation:</p> | ||
<p><ul> | ||
<li>O(1) or constant time: does not depend on the size of the input.</li> | ||
<li>O(n) or linear time: running time increases at most linearly with the size of the input.</li> | ||
<li>O(n2) or quadratic time: n to the power of 2.</li> | ||
</ul></p> | ||
<p>Scenarios: | ||
<ul> | ||
<li>worst case scenario: the longest possible time to solve the problem.</li> | ||
</ul> | ||
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<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script> | ||
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<h2 class="text-center">Bipartite graph</h2> | ||
<div class="panel panel-default"> | ||
<div class="panel-heading">Information</div> | ||
<div class="panel-body"> | ||
<p>We say that a graph G = (V, E) is bipartite if its node set V can be partitioned into sets X and Y in such a way that every edge has one end in X and the other end in Y.</p> | ||
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<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"> | ||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script> | ||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script> | ||
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<h2 class="text-center">Dynamic programming</h2> | ||
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<div class="panel-heading">Information</div> | ||
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<p>Dynamic Programming (DP) is an algorithmic technique for solving an optimization problem by breaking it down into | ||
simpler subproblems and utilizing the fact that the optimal solution to the overall problem depends upon the optimal | ||
solution to its subproblems.</p> | ||
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