Welcome to my GitHub profile!
I’m a passionate back-end developer and an aspiring Cloud Computing Security Expert. With extensive experience in back-end development and a keen interest in building secure, scalable solutions, I also work on applied Machine Learning projects that blend data science with production-ready deployment.

• Name: LiamBolt
• Profession: Back-End Developer & Cloud Computing Security Enthusiast
• Interests: Cloud Security, REST APIs, Automation, Machine Learning, and Continuous Learning
• Current Focus: Enhancing cloud security practices, mastering Infrastructure as Code (IaC), and productionizing ML models
• Contact: amwineliam@gmail.com

Explorations & Niche Frameworks: I also dive into Grammatical Frameworks (e.g., using Haskell) to broaden my programming perspective.

Here are some of my standout projects that highlight my skills, including my Machine Learning work:

• Mucosa Website
  Mucosa Website is a collaborative platform aimed at delivering an interactive and user-friendly online experience. My primary contribution was developing and optimizing the backend using Django and integrating APIs for improved performance.
  🔗 Mucosa Website

Below are ML projects I’ve developed — brief descriptions are included. (If you want exact repo links added, provide the repository names or allow me to pull them from your account and I’ll add direct links.)

• Stroke Prediction
  Predicting stroke risk from patient records using feature engineering, model selection (scikit-learn / XGBoost), evaluation with cross-validation, and deployment considerations (FastAPI + Docker).
  Key tools: Jupyter, pandas, scikit-learn, XGBoost, MLflow, Docker, FastAPI.

• Diabetes Prediction
  Supervised classification pipeline built with scikit-learn: preprocessing, hyperparameter tuning, model explainability (SHAP) and a simple API for inference.

• Image Classification / CNN Experiments
  Image models developed using TensorFlow and PyTorch for proof-of-concept classification tasks, with experiments tracked in MLflow.

• Customer Churn Prediction
  Data pipeline + modeling (feature stores, gradient boosting), model monitoring and simple CI for model retraining.

• Other ML Explorations
  Examples include credit-risk scoring, breast-cancer detection prototyping, and Kaggle-style end-to-end notebooks focused on data cleaning, EDA, and modeling.

I’ve worked on a variety of projects ranging from backend development to cloud solutions and ML. To see a complete list of my contributions, projects, and experiments, please visit my repositories page:

For a full list of my work, check out my repositories.

Here are some dynamic insights into my GitHub contributions:

I'm committed to deepening my expertise in cloud computing security and MLOps. My roadmap includes:

• Cloud Security Architecture: Mastering best practices and frameworks for secure cloud deployments.
• Infrastructure as Code (IaC) Security: Ensuring that automation and configuration tools meet stringent security standards.
• MLOps & Model Governance: Improving reproducibility, monitoring, and deployment practices for ML models.
• Certifications & Continuous Learning: Earning industry-recognized certifications in cloud security and completing advanced ML courses.

I aim to merge my development, cloud, and ML skills to build secure, production-ready intelligent systems.

I'm always excited to connect with fellow developers, security enthusiasts, and data scientists. Reach out to discuss collaboration opportunities, share ideas, or simply say hello!

• GitHub: LiamBolt
• Email: amwineliam@gmail.com
• LinkedIn: Amwine Liam Abaasa

Thank you for visiting my profile! Let's build secure and intelligent systems together.