Jekyll2026-05-28T18:41:09+00:00https://sachinkavindaa.github.io/feed.xmlSachin ChandrasekaraBioinformatics & Computational BiologySachin Chandrasekarasachikavindaa@gmail.comUnveiling Insights: A Beginner’s Guide to Exploratory Data Analysis (EDA)2023-12-10T00:00:00+00:002023-12-10T00:00:00+00:00https://sachinkavindaa.github.io/posts/2026/10/blog-post-1Exploratory Data Analysis, also known as EDA, is one of the most important steps in any data science project.

In this article, I explain the basic idea of EDA, why it is important, and how beginners can use it to find patterns, missing values, outliers, and useful insights from data.

You can read my full article here:

Unveiling Insights: A Beginner’s Guide to Exploratory Data Analysis (EDA)

Topics Covered

  • What is Exploratory Data Analysis?
  • Why EDA is important
  • Understanding dataset structure
  • Handling missing values
  • Detecting outliers
  • Visualizing data
  • Finding patterns and relationships
  • Preparing data for machine learning
]]>Sachin Chandrasekarasachikavindaa@gmail.comIntroduction to The Numerical Solution of IVP for ODE2021-08-21T00:00:00+00:002021-08-21T00:00:00+00:00https://sachinkavindaa.github.io/posts/2021/08/blog-post-2This article introduces the numerical solution of Initial Value Problems, also known as IVPs, for Ordinary Differential Equations, or ODEs.

Numerical methods are useful when exact analytical solutions are difficult or impossible to obtain. In this article, I discuss the basic idea behind solving ODEs numerically and explain how these methods help approximate solutions step by step.

You can read my full article here:

Introduction to The Numerical Solution of IVP for ODE

Topics Covered

  • Initial Value Problems
  • Ordinary Differential Equations
  • Numerical approximation
  • Step-by-step solution methods
  • Importance of numerical methods in applied mathematics

This article is useful for beginners who want to understand how numerical methods are applied to solve differential equations.

]]>Sachin Chandrasekarasachikavindaa@gmail.comNumerically Solving Systems of Ordinary Differential Equations (1st Order ODEs)2021-06-29T00:00:00+00:002021-06-29T00:00:00+00:00https://sachinkavindaa.github.io/posts/2021/06/blog-post-3Ordinary Differential Equations (ODEs) are widely used in mathematics, physics, engineering, biology, and many other scientific fields. In many real-world problems, systems contain multiple differential equations that must be solved together.

In this article, I introduce the basic idea behind numerically solving systems of first-order Ordinary Differential Equations and explain how numerical techniques can be used to approximate solutions step by step.

Topics Covered

  • Systems of first-order ODEs
  • Numerical approximation methods
  • Initial conditions
  • Step-by-step numerical solutions
  • Applications of differential equations

This article provides a beginner-friendly introduction for students interested in numerical analysis and scientific computing.

]]>Sachin Chandrasekarasachikavindaa@gmail.comOrdinary Differential Equation (ODE) by Python2021-06-16T00:00:00+00:002021-06-16T00:00:00+00:00https://sachinkavindaa.github.io/posts/2021/06/blog-post-4Python is a powerful programming language widely used for scientific computing and mathematical modeling. In this article, I introduce how Python can be used to solve Ordinary Differential Equations (ODEs) using numerical methods.

The article explains the basic concepts of ODEs and demonstrates how programming can help solve mathematical problems efficiently.

Topics Covered

  • Introduction to Ordinary Differential Equations
  • Numerical methods for solving ODEs
  • Solving equations using Python
  • Scientific computing basics
  • Mathematical modeling with Python

This article is useful for beginners who are interested in combining mathematics and programming for scientific problem solving.

]]>Sachin Chandrasekarasachikavindaa@gmail.com