Hi, I am Victor Sabare

Welcome to my personal blog where I share my thoughts and learnings. I am a data apprentice who is passionate about data science, machine learning and artificial intelligence. In my free time, I like developing side projects and learning new technologies.

This is my place for thoughts, reflections & everything in between. Have a good read!

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Published on
February 16, 2024 • –––views
The Role of Stochastic Processes in Data Science Innovation
stochasticprocesses machinelearning financialmodeling datascience predictiveanalytics uncertaintyquantification
This article delves into the sophisticated application of stochastic processes within data science. Readers will gain an advanced understanding of how randomness is modeled and utilized to enhance predictions and decision-making in complex, uncertain environments. From machine learning algorithms to financial market modeling, stochastic processes are pivotal in driving innovation and extracting meaningful insights from data.

Published on
February 8, 2024 • –––views
OLAP Cubes and Multidimensional Modeling with SQL Server Analysis Services.
dataanalytics SQL OLAP datawarehouse dataanalysis dataanalyst
In this article, you will learn about OLAP cubes and multidimensional modeling with SQL Server Analysis Services. This is a key concept for data analysts to understand, as it is a common way to store and analyze data in a data warehouse.

Published on
August 27, 2023 • –––views
Two Sample Proportion Tests | Comparing Population Proportions
Stastics Machine-Learning Data-Science
The article delves into the world of two-sample proportion tests, offering insights into comparing proportions between distinct populations. It explores both manual calculation and a more streamlined approach using Python's statsmodels library. From understanding the theoretical foundation of two-sample proportion tests to implementing them practically, readers gain a comprehensive understanding of how to assess significant differences in proportions within categorical data.

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