• 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

Saturday, March 25, 2023

Gaussian Naive Bayes

Naive Bayes is a fundamental Classification algorithm in the field of machine learning and data science. This probabilistic model, rooted in the principles of Bayesian statistics, is famous and useful for its efficiency, simplicity, and surprisingly robust performance across...
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Saturday, March 11, 2023

K-Nearest Neighbors Algorithm

The K-Nearest Neighbors (KNN) algorithm is a simple and powerful machine learning technique, it is often used for Classification tasks, but can be used for Regression tasks. In this post, I focus on the implementation of KNN algorithm for classification, because this is the...
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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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