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Hi πŸ‘‹, I'm Wonder Akwei

I am passionate about translating data into actionable insights

wonderakwei

citizenwonder

Connect with me:

citizenwonder wonderakwei @akweiwonder3

Languages and Tools:

aws azure bootstrap css3 docker git hadoop html5 javascript kafka mongodb mssql mysql nodejs opencv oracle pandas postgresql python pytorch scala scikit_learn seaborn tensorflow vuejs

wonderakwei

Β wonderakwei

wonderakwei

Wonder Akwei's Projects

real-time-news-website-with-javascript-and-news-api-integration icon real-time-news-website-with-javascript-and-news-api-integration

πŸ“° Developed a live news website using HTML, CSS, and JavaScript, fetching real-time data from the News API. This project demonstrates how to use async/await functions in JavaScript to integrate public APIs, creating a responsive and dynamic news aggregator.

real-time-pipeline-with-apache-flink-kafka-elasticsearch-and-docker icon real-time-pipeline-with-apache-flink-kafka-elasticsearch-and-docker

Ecommerce Sales Analytics Data Generation, developed a detailed system architecture using Apache Flink, Kafka, Elasticsearch, and Docker. Implemented real-time data streaming, established a robust, scalable data pipeline. Flink was set up, transactions were aggregated in Postgres and Elasticsearch, concluding with a dynamic streaming dashboard.

responsive-hamburger-menu-with-html-css-javascript icon responsive-hamburger-menu-with-html-css-javascript

This project is a simple and responsive hamburger menu designed for modern web applications. The menu is implemented using HTML, CSS, and JavaScript, and it provides a sleek and user-friendly navigation experience.

responsive-product-card-popup-modal icon responsive-product-card-popup-modal

This project demonstrates a card-based user interface with popup modals using HTML, CSS, and JavaScript. Each card represents a product, and clicking on a card opens a modal with more detailed information about the product.

salary-prediction-ml-deployment-app-with-streamlit icon salary-prediction-ml-deployment-app-with-streamlit

This project involves developing and deploying a salary prediction ML app using Streamlit. It includes steps from model creation to Streamlit interface. Explore 2020 Stack Overflow Developer Survey results for insights.

sales-marketing-data-analytics-using-python icon sales-marketing-data-analytics-using-python

This project utilizes Python, employing regression and correlation analysis to optimize marketing campaigns. By analyzing sales impact across different hospital account types, it unveils key strategies, culminating in actionable recommendations and a comprehensive ROI table for effective decision-making.

smart-chatbot-with-javascript-and-google-api icon smart-chatbot-with-javascript-and-google-api

This project demonstrates a chatbot built with HTML, CSS, and JavaScript, integrating Google’s Gemini API for responses. The chatbot features a sleek, responsive interface for a seamless user experience. It serves as a virtual assistant, understanding and responding to user queries in real time.

sql-case-study-sales-data-analysis icon sql-case-study-sales-data-analysis

Explored Data Mart's sales data, cleansed sales data, uncovered missing weeks, assessed yearly transactions, and delved into regional, platform, and demographic insights. Gained valuable perspectives on the impact of sustainable packaging on past sales performance.

streamlit-excel-data-management icon streamlit-excel-data-management

Excel data management with Python and Streamlit. Add, visualize, and analyze Excel records seamlessly. Features include auto-date, product ID generation, and basic analytics.

supply-chain-management-database icon supply-chain-management-database

Optimized business operations with a comprehensive database system. Streamlined inventory management, order processing, manufacturing processes, and logistics. Ensured quality control and efficient employee management for a seamless end-to-end solution.

telecom-customer-churn-prediction icon telecom-customer-churn-prediction

This project predicted customer behavior to retain Orange Telecom's valuable customers. Relevant data was analyzed, and a focused retention model was developed using the Churn Dataset. Models were built on customer activity data, indicating subscription cancellations.

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