Portfolio - Tenlancer

Gender Board Diversity on the Financial Performance

This research study aims to investigate the relationship between gender board diversity and financial performance in corporates operating in The Netherlands. The study explores the potential influence of having a diverse gender composition on the corporate boards and its impact on financial indicators such as profitability, return on equity, and stock performance. Through an extensive review of literature, data analysis, and statistical methods, this study provides insights into the significance of gender board diversity in the context of corporate financial performance.

Predicting Customer Churn

In this machine learning project, we implemented predictive modeling to forecast customer churn in the telecommunication industry. Leveraging a dataset containing customer behavior, demographics, and service usage, we applied various classification algorithms to identify potential churners accurately. The project’s objective was to assist telecom companies in proactively addressing customer retention strategies and enhancing their overall customer experience. Through this project, we demonstrated our expertise in machine learning and data-driven insights for effective decision-making.

Smart Home Automation using NodeMCU

This embedded systems project demonstrates the implementation of a smart home automation system using NodeMCU, an ESP8266-based development board. We developed a custom IoT (Internet of Things) solution to control and monitor various home appliances remotely through a mobile application. Leveraging the capabilities of NodeMCU and integrating it with sensors and actuators, we enabled seamless interaction and real-time data monitoring. The project aimed to showcase the potential of NodeMCU in building cost-effective and efficient smart home solutions. Through this project, we exhibited our expertise in embedded systems and IoT technologies, paving the way for a more connected and automated future.

Colour Sorting Device using Arduino Uno

In this Arduino project, we present a colour sorting device designed to automate the process of segregating objects based on their colours. Leveraging the capabilities of Arduino Uno microcontroller, RGB colour sensors, and servomotors, we developed an efficient and cost-effective colour sorting solution. The device scans the objects, detects their colours using RGB sensors, and swiftly sorts them into designated containers using servo-controlled mechanisms. The project showcases our expertise in Arduino programming, electronics, and automation, opening up possibilities for improving efficiency and accuracy in colour-based sorting applications. This project reflects our commitment to innovation and providing practical solutions for industrial and manufacturing processes.

Online Quiz Platform

In this captivating Flask web application project, we introduce an Online Quiz Platform designed to challenge and engage users in interactive quizzes. Leveraging Flask’s flexibility and Python’s capabilities, we developed a dynamic platform with multiple-choice questions from various topics. Users can register, choose quizzes based on their interests, and test their knowledge. The application offers real-time scoring and instant feedback on quiz completion. Administrators can manage quizzes, add new questions, and track user performance. The project showcases our expertise in web development, demonstrating how Flask can be used to create an interactive and educational platform that fosters continuous learning and intellectual exploration.

R Shiny Web Application: Interactive Data Visualization Dashboard

In this R Shiny web application project, we introduce an Interactive Data Visualization Dashboard that empowers users to explore and analyze data effortlessly. Leveraging the power of R Shiny, we created a dynamic platform where users can upload their datasets or select from pre-loaded samples. The application offers an array of customizable charts, graphs, and maps to visualize the data in real-time. Users can interact with the visualizations, apply filters, and gain valuable insights. The project showcases our expertise in R programming and data visualization, demonstrating how R Shiny can transform complex datasets into intuitive and interactive visual representations. This project aims to facilitate data-driven decision-making by providing users with a user-friendly and versatile data visualization tool.

Drone-Assisted Precision Agriculture: Transforming Farming Practices

In this pioneering project, we introduce the concept of Drone-Assisted Precision Agriculture, a game-changing approach that revolutionizes traditional farming practices. By harnessing the capabilities of drones, advanced sensors, and data analytics, we have developed an innovative solution for precision farming. Drones equipped with multispectral and infrared cameras can capture valuable data about crop health, soil moisture levels, and nutrient distribution. The collected data is then analyzed to generate actionable insights, enabling farmers to make informed decisions about irrigation, fertilization, and pest management. The project showcases our expertise in drone technology, remote sensing, and data analytics, demonstrating how Drone-Assisted Precision Agriculture can optimize crop yield, reduce resource wastage, and ultimately contribute to sustainable and efficient farming practices.