• K-Means

    Separating data into distinct clusters, organizing diverse information and simplifying complexity with vibrant clarity

  • Principal Components Analysis

    Making high dimensions comprehensible and actionable, it captures the maximum amount of variance in the data with a reduced number of features

  • Random Forest for Regression

    Combining decision trees, it provides predictive accuracy that illuminates the path to regression analysis

  • Support Vector Machines for Regression

    Leveraging mathematical precision, it excels in predicting values by carving precise pathways through data complexities

Thursday, April 20, 2023

Drawing the Line: Understanding Decision Boundaries

In the domain of data science, classification problems are everywhere. From identifying spam emails to diagnosing diseases, Classification algorithms have transformed the way we make decisions. Understanding and visualizing decision boundaries offers significant insights into...
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Saturday, April 8, 2023

Decision Trees for Classification

The Decision Tree algorithm is a powerful and versatile machine learning technique, it belongs to  supervised learning paradigm and is widely used for both Classification and Regression tasks, but is mainly used for classification problems. These algorithms work by...
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About Me

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I am a Physics Engineer graduated with academic excellence as the first in my generation. I have experience programming in several languages, like C++, Matlab and especially Python, using the last two I have worked on projects in the area of Image and signal processing, as well as machine learning and data analysis projects.

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Particle Swarm Optimization

The Concept of "Optimization" Optimization is a fundamental aspect of many scientific and engineering disciplines. It involves fi...

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