MachineLearningAlgorithms / templates /Test /Test-unsupervised.html
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{% extends "Test-layout.html" %}
{% block content %}
<h1 class="text-4xl font-bold text-gray-800 mb-6">Unsupervised Learning</h1>
<p class="text-gray-600 text-lg mb-8">Unsupervised learning is a type of machine learning that looks for previously undetected patterns in a dataset with no pre-existing labels and with a minimum of human supervision.</p>
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<h2 class="text-2xl font-semibold text-gray-800 mb-4">Clustering Algorithms</h2>
<p class="text-gray-600 text-lg mb-4">Used for grouping similar data points together.</p>
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<a href="/k-means-test" class="algorithm-box">K-Means Clustering</a>
<a href="/hierarchical-clustering-test" class="algorithm-box">Hierarchical Clustering</a>
<a href="/dbscan-test" class="algorithm-box">DBSCAN</a>
<a href="/gmm-test" class="algorithm-box">Gaussian Mixture Models (GMM)</a>
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<h2 class="text-2xl font-semibold text-gray-800 mb-4">Dimensionality Reduction Algorithms</h2>
<p class="text-gray-600 text-lg mb-4">Used for reducing the number of features in a dataset while retaining important information.</p>
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<a href="/pca-test" class="algorithm-box">Principal Component Analysis (PCA)</a>
<a href="/tsne-test" class="algorithm-box">t-Distributed Stochastic Neighbor Embedding (t-SNE)</a>
<a href="/lda-test" class="algorithm-box">Linear Discriminant Analysis (LDA)</a>
<a href="/ica-test" class="algorithm-box">Independent Component Analysis (ICA)</a>
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<h2 class="text-2xl font-semibold text-gray-800 mb-4">Association Rule Learning Algorithms</h2>
<p class="text-gray-600 text-lg mb-4">Used for discovering relationships between variables in large datasets.</p>
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<a href="/apriori-test#" class="algorithm-box">Apriori Algorithm</a>
<a href="/eclat-test" class="algorithm-box">Eclat Algorithm</a>
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{% endblock %}