Welcome to Toyin’s Data Science Projects, a blog dedicated to showcasing my passion for data science. Here, you’ll find a diverse portfolio of data science projects aimed at solving real-world challenges.

Exploring Spatial Transcriptomics

Right now, I am working in spatial transcriptomics, using advanced machine learning and AI techniques to understand gene expression within a tissue. This innovative work opens new doors in understanding how genes function across tissues and could revolutionise fields like personalized medicine and genomic research.

Broad Expertise in Data Science

However, my expertise extends beyond spatial transcriptomics. At Toyin’s Data Science Projects, I specialize in a range of data science techniques, including predictive modelling, deep learning, data visualisation, and statistical analysis. These skills allow me to tackle complex problems in various industries, from healthcare to finance. Through my projects, I demonstrate how data science can create impactful solutions to address real-world challenges.

Discover My Projects and Insights

On this blog, you’ll discover a collection of my projects, insights, and research. Explore my work in spatial genomics and other data science fields, such as AI applications and deep learning methods. Whether you’re interested in cutting-edge predictive modelling, spatial analysis, or the future of data science, you’ll find valuable insights here at Toyin’s Data Science Projects.

🏗️ Smart Waste Estimator (ML Application for Sustainable Construction)

This project demonstrates a practical application of machine learning to tackle sustainability challenges in the construction industry. The Smart Waste Estimator is a predictive model that estimates potential material waste based on project specifications like area, material type, and construction style.

✨ Built using Python, scikit-learn, and Streamlit, it showcases my ability to create real-world, user-facing ML tools. It’s part of my continued journey toward deploying ML in operational environments — particularly in sustainability and infrastructure.

Technologies Used:

  • Python, Pandas, scikit-learn
  • Streamlit (interactive app interface)
  • Power BI (visual reporting)
  • GitHub (for source control & documentation)
🔗 View Project on GitHub(in progress)
🚀 Try the Demo App (In progess)

Stay Updated

Stay tuned for regular updates featuring new research, AI applications, and collaborations. I frequently update this blog with new projects and insights to share my journey and keep you informed about the latest developments in my work.

Toyin's Data Science Projects t-SNE illustrating the spatial organisation of cells within a cancerous tissue
t-SNE illustrating the spatial organisation of cells within a cancerous tissue

Learn More About My Work

For more details about my background and expertise, visit the About Me page. If you have any questions or would like to collaborate, feel free to reach out through the Contact page.

External Resources

Read more about spatial transcriptomics in this research paper.
I use tools like TensorFlow and Scikit-learn in my projects.