Data Scientist
When applied to subscription businesses, one of the most important questions is: Which users are likely to leave, and why? In this project, I explored the KKBox dataset (a large Asian music streaming service) to answer that question. The work went beyond just predicting churn. I wanted to understand the drivers of churn and whether …
A machine learning model is a system that learns from data to make predictions or decisions without being explicitly programmed. If the data is flawed, the model’s decisions will be too. That’s why building responsible, fair AI isn’t just an ethical checkbox; it’s a critical part of building good technology. In this post, we’re going …
I started this project with a simple question:What makes a song a hit on Spotify?By the end, I had unintentionally walked through key lessons in descriptive analysis, confounding, matching, causal inference, and bootstrapping. This is what I learned, not just about the data, but about the mindset statistical analysis requires in the real world. Descriptive …
LangChain Ecosystem Overview LangChain is a powerful framework that simplifies the process of building applications powered by large language models (LLMs). Whether you’re using proprietary models like OpenAI or open-source alternatives like Hugging Face Transformers, LangChain provides a modular ecosystem to orchestrate prompts, chains, memory, agents, and tools, all under one roof. In this post, …
I recently participated in a Kaggle competition where the task was to detect AI-generated images vs. human-created ones. This story isn’t about my journey to becoming a Kaggle Grandmaster (though I do plan to be one someday 😉). It’s about what I learned while fine-tuning deep learning models — starting with ResNet18 and eventually switching …