Projects
Welcome to my project portfolio!
Here, you’ll find some of the personal projects I’ve worked on, showcasing my skills in data analysis, technical writing, and problem-solving. Each project reflects my passion for creating impactful solutions and my dedication to continuous learning.
Dashboards:
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This project showcases the sales data of a pie shop, analyzing various metrics such as customer preferences, sales trends, and inventory. It provides insights into which pies are most popular, helping to optimize inventory and sales strategies.
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Street Fighter: Power BI Dashboard
In this project, I recreated the popular Street Fighter dashboard by Power BI Park using Power BI, showcasing various game statistics and player performance metrics. The dashboard provides an interactive view of data such as win rates, character selection, and match outcomes.
Featured Projects:
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A personal portfolio website built using Docusaurus, designed to showcase my professional journey, projects, and technical writing. The site features a clean, user-friendly interface and serves as a central hub for sharing my work and connecting with others.
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Getting Started in Technical Writing
This project is a compilation of resources for anyone looking to get started or deepen their knowledge in technical writing. If you find it helpful, we’d greatly appreciate a star ⭐ to show your support!
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Microsoft Fabric: How to Build a Customer Segmentation Project
This project demonstrates how to create a Lakehouse using the Kaggle API to store a mall dataset, followed by data transformation using Data Wrangler. We’ll then perform customer segmentation with the KMeans clustering algorithm, grouping customers based on annual income and spending scores into categories like low, average, and high-income spenders.
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How to Send SMS with Messaging API and OpenAI API Honestly, one of my favourite 💙 projects.
This project will show you how to build a word-of-affirmation service SMS application using the Twilio Programmable Messaging API and the OpenAI API. The application you build will send positive messages to users, one with predefined messages and another that generates new messages with OpenAI's GPT-3 model.
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Telegram bot: Message @CozeReceipeGeneratorbot on Telegram Another one of my favourite 💙 projects.
Developed a Telegram bot using Coze that offers personalized recipe suggestions through AI-driven interactions. The bot leverages natural language processing to generate recipes based on user preferences, providing a seamless and interactive experience.
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In this project, you'll learn how to create Plugins from scratch in Coze, extending the functionality of your application without altering the core source code. Plugins serve as a bridge between your application and the broader technological ecosystem, allowing for seamless integration with other tools and services.
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Building a LinkedIn Profile Location Tracker with The Social Proxy
This project walks you through building a LinkedIn profile location tracker using The Social Proxy’s scraper to extract profile data and map movements with a geolocation lookup API. You’ll also learn how to visualize the tracked locations using Leaflet.js for an interactive mapping experience.
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Build Retrieval-Augmented Generation (RAG) with Milvus
This project teaches how to build Retrieval-Augmented Generation (RAG) systems using Milvus, allowing developers to manage hallucinations and embed similarity searches in large language models (LLMs). The guide walks through leveraging unstructured data for more accurate and efficient information retrieval in RAG applications.
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Scarping CNN’s homepage using The Social Proxy’s scraper
This project demonstrates how to scrape CNN’s homepage using The Social Proxy’s scraper and Python to extract headlines and metadata, bypassing anti-bot measures with a mobile proxy. You’ll also learn how to organize the scraped data into a structured format, such as JSON, for further analysis or integration into tools like news aggregators or sentiment analysis applications.
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Retrieval-Augmented Generation (RAG) with Milvus and LlamaIndex.
This project demonstrates building a Retrieval-Augmented Generation (RAG) system using Milvus and LlamaIndex to integrate private and public data, enhancing the output of large language models (LLMs). By efficiently handling unstructured data and improving information retrieval, this solution bridges the gap between siloed data and large-scale public information.