noturlee Goto Github PK

followers: 11.0 following: 4.0 repos: 20.0 gists: 0.0

Name: Leighché Jaikarran

Type: User

Company: HeroMed

Bio: Full-Stack Developer at HeroMed, passionate about Data Science. Specialising in Business Intelligence and Artificial Intelligence.

Location: Durban

Blog: https://leighche.co.za

Hi 👋, I'm Leighché

A passionate aspiring BI Architect from the beautiful South Africa

Leighché's GitHub Readme Stats

Brief About me

🔭 I’m currently working on Medical Software & API's
🌱 I’m currently learning Data Analytics
👯 I’m looking to collaborate on Anything Full-Stack
👨‍💻 All of my projects are available at https://github.com/noturlee/noturlee/
📝 I regularly write articles on https://www.linkedin.com/in/leighché/
💬 Ask me about React, Java,C#, Oracle, SSMS/MySQL, Power BI
📫 How to reach me [email protected]
📄 Know about my experiences https://www.linkedin.com/in/leighché/
⚡ Fun fact I love Pokémon

Why I Chose Business Intelligence

I pursued a Bachelor of Computer and Information Science degree, and as I approached the point of specialization, I realized that a traditional software development role wasn't the right fit for me. I excelled in UI/UX design, but found that it didn't have the demand I was looking for and it was too easy for me. Similarly, coding in a software development space was also straightforward; I was too good at it and yearned for something more challenging and versatile.

I sought a path that offered more versatility and the opportunity to integrate into various industries. Business Intelligence (BI) stood out to me as a field that not only matched my aspirations but also piqued my interest due to its strong connection with data science and analytics. The ability to leverage data to drive meaningful business decisions fascinated me. Additionally, I was intrigued by how Artificial Intelligence (AI) and Machine Learning (ML) integrate with BI, enhancing the ability to analyze vast datasets and uncover hidden insights.

This interest motivated me to select electives focused on BI during my postgraduate honors program. Choosing Business Intelligence has allowed me to combine my technical skills with strategic thinking, providing a fulfilling and dynamic career path. I am passionate about the impact of data-driven insights and look forward to continuing my journey in this ever-evolving and impactful domain, especially as AI and ML continue to expand the possibilities within BI.

📕 Top Projects I've Contributed To

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Leighché Jaikarran's Projects

agrienergy-connect

A forward-thinking initiative bridging agriculture and green energy in South Africa. As an MVC platform, it fosters sustainable practices and integrates renewable energy solutions. It serves as a vital link between farmers and technology providers, driving innovation for a greener future.

autogrow-website

AutoGrow is a hydroponics team that came together as part of their Work Integrated Learning, which is a module for the institution known as Varsity College. The team consists of six members and is lead by Leighché Jaikarran

azure-carrental-app

cldv6211---poe-Leighche created by GitHub Classroom

azure-functions-medical-system

Http and Queue Triggers, that relayed information from a local console application to Azure which then trigged a Queue trigger and Http Trigger which then sorted placed the information of patients after validation within the trigger into an Azure Database as well as Blob storage and Azure Tables

elegantnails

website blends cutting-edge HTML animations with captivating visuals to showcase our premium nail services. Explore the gallery of stunning nail designs, watch our talented artists in action through dynamic videos, and schedule your appointment seamlessly with our user-friendly booking system

imdb-dataanalysis

A data model that predicts the IMDb rating of a movie based on features like genre, director, and actors. Using regression techniques to tackle this problem.

iris-dataanalyis

This project aims to classify Iris flowers into three species—setosa, versicolor, and virginica—based on their sepal and petal measurements using machine learning techniques. The dataset comprises 150 samples evenly distributed among these species

leighches-personal-profile

librare.io-online

Librare.io is a modern MVC ASP.NET Core .NET 8.0 application designed as an interactive online library with a Steven Universe theme, users can add their books that inspire tem the way steven inspires Leighché and create a serene space

library-console-app

A library application for CRUD, showing iterative development from basic console application, to advance console application to windows presentation foundation application ready for publication

microbit-remote

A Kotlin application that controlls the MacqueenPlus V2 robot, using http requests, connecting via a wifi modul (ESP-01) connected on the robot.

mvc-tutorial

This Github repo is designed to explain MVC Framework and how it integrates to the local database on your local machine, covering topics like Scaffolding and Methods

noturlee

psychologist-site

sales-dataanalysis

This project aims to predict product sales based on advertising expenditures, focusing on 'TV advertising'. Machine learning techniques are employed to analyze and interpret data, enabling businesses to optimize advertising strategies and maximize sales potential.

security-company-website

student-records-management-app

a C# application that connects to a SQL database for student and lecturers , managing student records, capturing marks, and tracking student modules, seperate functionality as per roles

task-tracking-web-app

TaskTracker is a MVC ASP.NET Core Web application which allows students to monitor and take control of their studies, and create a way to manage it using CRUD

tasktracker-windows-app

This is a standalone desktop time management application built using C# and Windows Presentation Foundation (WPF). The application allows users to manage their academic schedule for a semester, including adding modules, tracking self-study hours, and calculating remaining self-study hours for each module

titanic-datamodel

This project demonstrates the process of data preprocessing, model training, evaluation, and tuning in building a predictive model for a classic dataset. The Random Forest model, with its ability to handle complex relationships and interactions between features, proved to be the most effective in this case.