Daughter of the Sea

1. Introduction In various fields, from academia to marketing to government, analyzing survey data is essential. Yet, for many, it's a daunting task requiring technical skills and time-consuming learning curves. Recognizing this, I've developed a user-friendly program tailored for non-tech individuals. By simplifying the analysis process, it eliminates the need for extensive training, making data analysis accessible to all.  2. Features The program offers a range of powerful features, each designed to simplify survey data analysis and provide tangible benefits to users: No Installation Required: Accessible directly through Google Drive, our program runs seamlessly in Colab Notebooks, eliminating complex setups. Simple Interface: With just a Google Drive account, users can effortlessly initiate analysis, reducing the learning curve. Comprehensive Analysis: Offering both quantitative and qualitative analysis, users can uncover demographic insights, trends, and patterns, as wel...

1. Introduction In today's business landscape, organizations rely heavily on complex enterprise resource planning (ERP) systems like SAP to manage their operations effectively. However, as these systems grow in scale and complexity, it becomes increasingly challenging to identify and optimize the intricate relationships between various business entities. One of the primary challenges faced by organizations using SAP is the lack of visibility into the relationships and dependencies between different business entities. These entities, which can include customers, products, orders, and suppliers, are often spread across multiple systems and modules within the SAP ecosystem. Without a clear understanding of how these entities are interconnected, it becomes difficult to identify bottlenecks, streamline processes, and optimize overall system performance. This project aimed to address these challenges by developing a user-friendly web application that provides a comprehensive view of the ...

Heart Failure Prediction using Machine Learning In this project, I investigated various programming and analytical methods for analyzing and evaluating the effectiveness of machine learning models in accurately predicting patient cases of heart failure. The healthcare sector relies on precise predictions of heart failure cases to make well-informed decisions about patient survival. I used scientific computing, data analysis, data visualization, and machine learning techniques to complete this task.  The project demonstrated my proficiency in using various machine learning techniques, data analysis, and visualization tools to tackle a real-world problem in the healthcare domain. It showcases my ability to identify and address challenges, such as class imbalance, and use feature selection methods to improve model performance. To view coding, please follow this link. Note: Please, click on the below images to view them with better clarity. I. IMPLEMENTATION 1.1. Exploratory Data ...

In my dissertation project, I utilize the Google Maps API, Natural Language Processing and Big Data Techiques to analyze restaurant reviews in London. By examining both quantitative and qualitative data, I uncover valuable insights for economic observers, restaurant owners, and customers alike. This analysis offers a procedural framework for deriving meaningful conclusions from Google Maps reviews, benefiting various stakeholders in the restaurant industry.  Disclaimer: The purpose of this project is to focus on academic pratice, not for economic or trading purposes. The information provided is approximate and not 100% accurate. Because the data used in this project was collected in June 2023, To view coding of this project, please follow this link .  Note: Please, click on the below images to view them with better clarity. I. OBJECTIVES:  - To analyze restaurant distribution patterns in London, which contribute to a deeper understanding of the city's culinary geography -...