Ivan Ivani, PhD.

Ivan Ivani, PhD.

Data Scientist

Posts by Tags

A/B testing

A/B testing - principles and practicalities on how to setup the experiment

12 minute read

Published:

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.

AI agent

An easy to implement AI Voice and Video Agents with Livekit: A Straightforward Approach

6 minute read

Published:

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.

CTAS

Beyond the SQL Basics - Mastering Advanced SQL Constructs

4 minute read

Published:

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.

CTEs

Beyond the SQL Basics - Mastering Advanced SQL Constructs

4 minute read

Published:

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.

Cpk

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

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.

Data

Crafting a Standout Data Analyst Portfolio

4 minute read

Published:

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.

Data Analysis

Crafting a Standout Data Analyst Portfolio

4 minute read

Published:

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.

Mastering the Art of Data Cleaning

6 minute read

Published:

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.

Data Cleaning

Mastering the Art of Data Cleaning

6 minute read

Published:

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.

Data Science

A/B testing - principles and practicalities on how to setup the experiment

12 minute read

Published:

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.

Data Science roadmap in 2024

Becoming a Data Scientist in 2024: Roadmap

3 minute read

Published:

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.

Guide

Becoming a Data Scientist in 2024: Roadmap

3 minute read

Published:

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.

LLM

An easy to implement AI Voice and Video Agents with Livekit: A Straightforward Approach

6 minute read

Published:

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.

Livekit

An easy to implement AI Voice and Video Agents with Livekit: A Straightforward Approach

6 minute read

Published:

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.

Molecular Dynamics

Neural Network Force Fields for Molecular Dynamics Simulations: A Comprehensive Review

29 minute read

Published:

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.

Neural Networks

Neural Network Force Fields for Molecular Dynamics Simulations: A Comprehensive Review

29 minute read

Published:

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.

Overview

Neural Network Force Fields for Molecular Dynamics Simulations: A Comprehensive Review

29 minute read

Published:

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.

Parameterization

Neural Network Force Fields for Molecular Dynamics Simulations: A Comprehensive Review

29 minute read

Published:

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.

Portfolio

Crafting a Standout Data Analyst Portfolio

4 minute read

Published:

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.

Mastering the Art of Data Cleaning

6 minute read

Published:

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.

Ppk

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

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.

Projects

Crafting a Standout Data Analyst Portfolio

4 minute read

Published:

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.

Mastering the Art of Data Cleaning

6 minute read

Published:

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.

PySPC

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

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.

Quality Control

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

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.

Six Sigma

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

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.

advanced

Beyond the SQL Basics - Mastering Advanced SQL Constructs

4 minute read

Published:

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.

anomaly detection

business

collect

Data Pipelines basics - the backbone of data apps

6 minute read

Published:

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.

compute

Data Pipelines basics - the backbone of data apps

6 minute read

Published:

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.

data analytics

SQL - The most used tool among Data Scientist and Analysts

7 minute read

Published:

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.

data engineering

Data Pipelines basics - the backbone of data apps

6 minute read

Published:

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.

data pipeline

Data Pipelines basics - the backbone of data apps

6 minute read

Published:

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.

data-driven

A/B testing - principles and practicalities on how to setup the experiment

12 minute read

Published:

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.

decision making

A/B testing - principles and practicalities on how to setup the experiment

12 minute read

Published:

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.

essentials

SQL - The most used tool among Data Scientist and Analysts

7 minute read

Published:

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.

first principles

force-fields

Neural Network Force Fields for Molecular Dynamics Simulations: A Comprehensive Review

29 minute read

Published:

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.

freud detection

http requests

hypothesis

A/B testing - principles and practicalities on how to setup the experiment

12 minute read

Published:

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.

ingest

Data Pipelines basics - the backbone of data apps

6 minute read

Published:

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.

machine learning

manufacturing

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

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.

predictions

problem solving

process

Data Pipelines basics - the backbone of data apps

6 minute read

Published:

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.

programming

queries

SQL - The most used tool among Data Scientist and Analysts

7 minute read

Published:

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.

sepsis

sql

Beyond the SQL Basics - Mastering Advanced SQL Constructs

4 minute read

Published:

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.

SQL - The most used tool among Data Scientist and Analysts

7 minute read

Published:

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.

subqueries

Beyond the SQL Basics - Mastering Advanced SQL Constructs

4 minute read

Published:

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.

unsupervised model

views

Beyond the SQL Basics - Mastering Advanced SQL Constructs

4 minute read

Published:

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.

voice assistant

An easy to implement AI Voice and Video Agents with Livekit: A Straightforward Approach

6 minute read

Published:

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.