Iβm steadily building my path toward becoming a data scientist β one experiment, one lesson, and one repo at a time.
This is where I share my journey through hands-on projects, structured paper reviews, and daily idea generation.
- π§ Building end-to-end machine learning pipelines (EDA β modeling β tuning β evaluation)
- πΈ Real-time image classification with CNNs and OpenCV
- π§ͺ Deep learning experiments from textbooks and papers
- π Strengthening AI, statistics, and data science foundations through coursework
- Languages: Python Β· Markdown Β· Git
- Libraries: pandas Β· NumPy Β· scikit-learn Β· Matplotlib Β· Seaborn Β· TensorFlow Β· Keras Β· OpenCV
- Topics: Data Analysis Β· Machine Learning Β· Deep Learning Β· Computer Vision Β· Feature Engineering Β· Model Tuning
- Learning Interests: Transfer Learning Β· SHAP/XAI Β· Model Deployment Β· Real-world Data Storytelling
- Computer Vision Projects β Real-time classification, image crawling, CNNs
- Machine Learning Projects β Tabular data, ensembles, Optuna tuning
- Ideas β Daily creative sparks and project seeds
- Paper Reviews β Structured summaries and experiments
Every repo is a checkpoint in my growth:
- Early experiments β quick EDA, visualization, first ML models
- Research notes β in-depth paper reviews, structured markdown logs
- Full projects β end-to-end pipelines, deployable apps, competition work
- Blog: hojjang98.github.io
- π« Reach me anytime β letβs connect and share ideas!