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lka1459/README.md

Hi, I'm Luka 👋

🎓 Artificial Intelligence student at UTS
💻 Assistant IT Support Technician
🤖 Aspiring Machine Learning Engineer

🚀 About Me

  • Currently working in IT support and building technical experience
  • Passionate about Machine Learning, AI systems, and cybersecurity
  • Working towards becoming a Machine Learning Engineer
  • Building projects and improving my Python & data skills

💻 Tech Stack:

Python JavaScript TypeScript Java PowerShell HTML5 CSS3 Windows Terminal Azure SQLite Postgres Matplotlib NumPy Pandas scikit-learn Scipy Plotly Streamlit GitHub Git

📂 Projects

🤖 Tic Tac Toe AI

  • Built an AI agent using the Minimax algorithm
  • Implemented game logic and decision-making in Python
  • Ensured optimal gameplay through exhaustive search

💳 Credit Card Fraud Detection

  • Developed machine learning models to detect fraudulent credit card transactions
  • Implemented Logistic Regression, Random Forest, and XGBoost classifiers
  • Applied SMOTE and machine learning pipelines to address class imbalance
  • Evaluated performance using Precision, Recall, F1-Score, and Precision-Recall AUC
  • Performed hyperparameter tuning and model comparison
  • Visualised model performance using Precision-Recall curves

🛒 Olist Customer Analytics & Churn Prediction

  • Built a customer analytics pipeline using SQLite, SQL, pandas, and scikit-learn
  • Engineered customer-level features from multiple relational tables using SQL
  • Developed a machine learning model to predict customer churn
  • Applied feature engineering, preprocessing pipelines, and model evaluation techniques
  • Created an interactive Streamlit application for model predictions and customer insights

🛡️ Cybersecurity Analytics Dashboard (In Progress)

  • Building a cybersecurity analytics platform using PostgreSQL, Python, SQL, and Streamlit
  • Importing and managing network traffic datasets within a PostgreSQL database
  • Developing SQL queries and views to analyse network events and security metrics
  • Creating interactive dashboards to visualise cybersecurity trends and attack patterns
  • Preparing the platform for future anomaly detection and intrusion detection models

📊 Data & Python Projects

  • Pokémon Data Explorer (pandas-based data analysis and filtering)
  • CSV Data Summariser (automated statistical reporting)
  • Log Analyser (regex-based log parsing and analysis)
  • File Organiser (file system automation and categorisation)
  • Discord Soundboard Bot (Python and discord.py)

🎯 Goals

  • Build strong Machine Learning portfolio
  • Transition into AI / ML roles
  • Learn advanced ML frameworks (TensorFlow, PyTorch)

🌐 Connect with Me

⭐️ Always learning and building

Pinned Loading

  1. email-spam-classifier email-spam-classifier Public

    Email spam classifier built with scikit-learn, comparing Logistic Regression and Naive Bayes on text data.

    Jupyter Notebook

  2. salary-estimator salary-estimator Public

    Salary prediction regression model that compares Linear regression with Support Vector Regression.

    Jupyter Notebook

  3. customer-churn-prediction customer-churn-prediction Public

    SQL and machine learning project using the Olist E-Commerce dataset to analyse customer behaviour, engineer features with SQLite, and build customer churn prediction models.

    Jupyter Notebook