- Learning Record Introduction
- Why Data Science
- Data Science Projects
- SQL
- Data Structure & Algorithm
- Certificates
- General Helpers
- Conclusion
- Contact Information
- License
Welcome to my Learning Record! This repository is a personal testament to my journey into the exciting world of Artificial Intelligence and Data Science. It showcases my dedication to understanding and leveraging these fields to gain insights, build intelligent systems, and make informed decisions.
In this era of vast and ever-growing data, AI and data science combine disciplines like statistics, data analytics, machine learning, and particularly deep learning, to uncover hidden patterns and insights by processing large datasets. These technologies allow us to build models that learn from data, enabling intelligent predictions, decisions, and innovative applications.
What excites me most is the potential of deep learning to go beyond predictions and create real-world innovations and intelligent tools. The ability to use this technology to build smarter systems that can transform daily life, whether by improving convenience or enabling entirely new solutions, drives me to master the core techniques behind it and make a meaningful impact in this data-driven and AI-powered world.
The Projects folder contains a collection of my hands-on work across various domains of machine learning and data science. These projects reflect my practical application of data science concepts, from exploratory data analysis to machine learning and deep learning.
Here are three highlighted projects that showcase different aspects of my skills:
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🐾 PawMatchAI – A deep learning project for dog breed classification with over 13k+ GPU Runs and 31k+ visits, and was featured in Hugging Face's "Spaces of the Week" for its strong user engagement and real-world utility. It combines ConvNeXtV2, Multi-Head Attention, and a morphological feature extractor to accurately classify 124 breeds, and uniquely offers a sophisticated recommendation system to suggest the most compatible match based on detailed lifestyle preferences and breed characteristics. The project demonstrates advanced problem-solving by implementing knowledge distillation techniques to address challenging breed distinctions and integrating contrastive loss functions to enhance model robustness against visually similar breeds.
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🛰️ Vision Scout – A sophisticated multi-modal computer vision system that orchestrates YOLOv8, CLIP, Places365, and Llama 3.2 through intelligent fusion architecture. The system transcends traditional object detection by integrating environmental scene classification, semantic context analysis, and advanced natural language generation to transform visual data into comprehensive narrative descriptions. Vision Scout performs spatial mapping, functional zone identification, lighting analysis, and activity inference while maintaining factual accuracy through structured LLM enhancement processes. The platform supports both static image analysis with detailed scene interpretation and foundational video processing capabilities for temporal object tracking.
Currently, the project has accumulated 9k+ visits and 3.7k+ GPU runs on Hugging Face. Recognition as a featured project in Hugging Face's "Spaces of the Week" demonstrates its innovative approach to bridging computer vision and natural language understanding for practical applications.
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💳 Credit Card Fraud Detection - A traditional machine learning project tackling highly imbalanced data to detect fraudulent transactions. Using advanced techniques like ADASYN sampling and XGBoost with Bayesian hyperparameter optimization, this project achieved a 99% AUC score, showcasing my skills in data preprocessing and model evaluation.
Each project represents a step towards honing my skills and deepening my understanding of how data can be used to solve real world problems.
This section contains a variety of SQL challenges that I have tackled, showcasing my ability to manipulate and query databases effectively.
Practicing these exercises has enhanced my SQL skills, improving my ability to handle structured data efficiently and extract meaningful insights from databases.
The Data Structure and Algorithm folder is dedicated to documenting my journey through various algorithmic challenges and data structure problems.
Each entry includes a problem description, the solution approach, and Python code implementations.
This section aims to enhance my problem-solving skills and deepen my understanding of fundamental computer science concepts.
The Certificates folder is a record of the formal education and training I have completed in the field of Data Science.
These certificates represent not just the acquisition of knowledge, but my commitment to continuous learning and professional growth in this rapidly evolving field.
Here, you'll find a treasure trove of handy functions designed to make your data science and machine learning journey smoother and more enjoyable. Whether you're crunching numbers, visualizing data, or building models, my collection of helpers is here to save you time and effort.
These General Helpers are crafted with care to tackle a variety of tasks, big and small. They're like trusty sidekicks, ready to assist in the most efficient way possible. Forget about repetitive boilerplate code—these functions are tested, optimized, and eager to jump into action.
Imagine having a toolbox filled with all the right tools to get the job done faster and better. Explore the examples provided to see how these helpers can seamlessly fit into your workflow. I've included practical demonstrations to help you get started quickly. Whether you're a beginner or a seasoned pro, you'll find these tools invaluable.
Feel free to explore, experiment, and expand your toolkit with my General Helpers. Contributions and suggestions are always welcome! Let's build something amazing together! Happy coding! 💻✨
Through Data Science, I aspire to make meaningful contributions by transforming raw data into actionable insights.
This Learning Record is not just a showcase of what I have achieved, but a reflection of my ongoing journey to understand more about the world through the lens of data.
For any questions or suggestions about my project, please feel free to contact me at:
© 2025 Eric Chung. This project is licensed under the Apache License 2.0, a permissive open source license that enables broad usage while ensuring proper attribution to the original author.
For detailed terms and conditions, please refer to the LICENSE file.