Machine Learning Models for Sepsis Prediction: Research, Development Strategies, and Implementation
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Blog posts
2025
Neural Network Force Fields for Molecular Dynamics Simulations: A Comprehensive Review
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In recent years, there has been a surge in research in classical Molecular Dynamics and force-field parameterization using advanced machine learning like Neural Networks. Since this has been the topic of my PhD work, I wanted to explore the field and try to summirize recent advancing in this field. For this I wanted to test Gemini Research feature. Thus, this post is written by Gemini, and the results are very interesting.
A/B testing - principles and practicalities on how to setup the experiment
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One of the most common Data Scientist requeriments nowadays is A/B testing, also known as split testing. A basic scientific method, A/B testing is a fundamental technique in data-driven decision-making, widely used in marketing, product development, and user experience optimization. It involves comparing two versions of a webpage, email campaign, or app feature to determine which performs better based on key metrics such as conversion rates, engagement, or revenue. By systematically testing variations and analyzing statistical significance, businesses can make informed changes that improve user experience and drive growth.
Beyond the SQL Basics - Mastering Advanced SQL Constructs
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For data scientists and analysts, basic SQL queries are just the starting point. To truly unlock the power of databases and perform complex analyses, you need to delve into advanced constructs. This blog post explores five essential techniques: Subqueries, Common Table Expressions (CTEs), Views, Temporary Tables, and Create Table As Select (CTAS). These tools enable you to write more efficient, readable, and powerful SQL code.
Data Pipelines basics - the backbone of data apps
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Data is everywhere, like a river flowing into a city. But raw data, like river water, isn’t always ready to use. We need to clean it, process it, and get it where it needs to go so it can be helpful. That’s why data pipelines are important.
An easy to implement AI Voice and Video Agents with Livekit: A Straightforward Approach
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In this blog post, we will discuss the implementation of AI-powered voice and video agents using the Livekit platform. Our experience demonstrates that setting up these agents is a straightforward process, especially with the comprehensive documentation and tutorials available on the Livekit website. We have successfully implemented two versions of these agents: one focused solely on voice interaction and another that incorporates both voice and visual assistance.
2024
Crafting a Standout Data Analyst Portfolio
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A well-constructed portfolio is your golden ticket to showcasing your data analysis skills and landing your dream job. It serves as a window into your expertise, showing potential employers not just what you’ve done but how you think, solve problems, and communicate results. Let’s break down the essential elements of a standout data analyst portfolio and explore how to build one that truly stands out.
Analyzing Manufacturing Data - Cpk and Six Sigma
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I’ve been working in Automotive manufacturing for more then a year now and there is one concept that is holy grail in this industry, and that is Six Sigma. It’s a methodology for achieving near-perfect quality in manufacturing. But how can you could leverage Six Sigma tools right from your Python environment? That’s where the manufacturing package comes in.
Anomaly detection in http requests
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SQL - The most used tool among Data Scientist and Analysts
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In the world of data analysis, SQL (Structured Query Language) is the fundamental rock. It’s the language that allows you to communicate with databases, extracting, manipulating, and analyzing data with precision. Whether you’re a seasoned analyst or just starting your journey, a solid grasp of SQL is essential for uncovering meaningful patterns and driving data-informed decisions. This blog post will cover the fundamental concepts of SQL, basic query structures, and the software tools that empower data analysts. But first let’s answer what is a database and what are two main categories of databases.
Mastering the Art of Data Cleaning
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As data analyst, people often ask me where do I spend most of my work time, besides scrolling through the internet. When people think about data analysis, they often imagine building predictive models or creating dazzling visualizations. But beneath the surface of every successful data project lies an essential yet often underestimated step: data cleaning. This critical process lays the foundation for trustworthy insights, making it one of the most valuable skills for any data professional.
Becoming a Data Scientist in 2024: Roadmap
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As the data landscape continues to evolve in 2024, becoming a data scientist requires a multi-faceted approach, encompassing coding, mathematical proficiency, data analysis, and machine learning. This guide outlines a comprehensive roadmap to becoming a proficient data scientist, integrating essential skills and modern practices such as working with Large Language Models (LLMs) and prompt engineering.
First Principles Thinking in everyday life
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