Welcome to my repository, where I showcase a diverse collection of projects developed over the past two years as part of my academic journey at RMIT University. Each project reflects my commitment to mastering the intricacies of applied analytics, harnessing the power of data to derive actionable insights and solve complex problems. Utilizing the R programming language, I have explored various domains, encompassing data wrangling, time series analysis, and machine learning.
Through these projects, I have not only honed my technical skills but also cultivated a profound understanding of how data can be leveraged to inform decisions and drive innovation across different sectors.
- Applied Analytics: Dive into projects that demonstrate the application of statistical and analytical methods on real-world datasets, showcasing how data-driven insights can enhance decision-making processes.
- Data Wrangling: Explore my work on cleaning, transforming, and organizing raw data into structured formats, ensuring that the data is ready for analysis and effectively highlights its underlying patterns.
- Time Series Analysis: Examine analyses of data points collected over specific time intervals, where I investigate trends, seasonality, and forecasting to uncover valuable insights from temporal data.
- Machine Learning: Discover projects involving predictive modelling and the implementation of machine learning algorithms, where I develop models that learn from data to make informed predictions and automate decision-making processes.
This repository not only serves as a reflection of my academic accomplishments but also as a testament to my passion for data analytics and research. I invite you to explore these projects and engage with the insights and methodologies presented within.
The projects reflect my interests in:
- Healthcare: Analyzing healthcare data to derive insights and support decision-making, including forecasting and predictive analytics.
- Investment Analysis: Exploring financial data and investment strategies, with a focus on tweaking existing codes to generate new insights.
- Transport: Problem-solving through data analysis to optimize transport systems and enhance efficiency.
- Temperature Prediction: Utilizing analytics for accurate temperature forecasting and understanding climatic trends.
- Housing Crisis: Leveraging data analysis to address the housing crisis and study market dynamics.
- Food Allocation and Agriculture: Implementing best practices in agriculture and optimizing food distribution using data-driven approaches.
- Bayesian Logistic Regression Analysis for Stroke Prediction: Analyzing Risk Factors, Gender Differences, and Health Conditions
- Time Series Analysis - Melbourne Traffic Outlook
- Time series Analysis - Melbourne Temperature Anomalies