• 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

Wednesday, February 22, 2023

Classification in Machine Learning

Classification is a fundamental task in the field of Machine Learning and Data Science. As one of the most widely applied areas of machine learning, classification algorithms extract valuable insights from data. In this post, I will go deeper into the world of classification,...
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Sunday, February 12, 2023

EDA - Customer Segmentation

Marketing campaigns play a crucial role in promoting products and services, and understanding the behavior of customers is essential for designing effective strategies. In this post, I conduct an Exploratory Data Analysis (EDA) on a marketing campaign dataset. The goal is to gain insights into customer behavior and uncover patterns that can inform...
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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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