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One of the hardest tasks that an assessor has to face in their professional career is High-Dimensional Data Visualization. And there’s a good reason for this, because visualisations are a vital tool for communicating findings, providing feedback, and enabling others to understand results. So if you’re assigned a T-SNE (t-SNE or t-Distributed Stochastic Neighbor Embedding) visualisation, you’re going to face a daunting task. Before diving into this topic, let me give
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The t-SNE visualization is one of the most popular and effective visualization methods to analyze high-dimensional data. It is often employed in machine learning and data science to help you discover the underlying relationships among data points, clusters, and dimensions. In this article, we will learn about the t-SNE visualization and its applications, as well as the pros and cons of using this visualization technique. Pros: – Easy to understand and apply. – Effective for analyzing large datasets. – Provides clear visual representations of complex
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