Data Science & ML Insights
Exploring analytics, machine learning, trading, and AI. Check my CV for my professional background.
Recent Posts
Exploratory Data Analysis Best Practices for Data Scientists
Published: at 12:00 AMA practical framework for conducting rigorous exploratory data analysis — from profiling distributions and detecting outliers to uncovering feature relationships before model training.
Prompt Engineering Techniques That Actually Work for LLMs
Published: at 12:00 AMA practitioner's guide to prompt engineering — covering chain-of-thought, few-shot examples, structured output, and retrieval augmentation to get reliable, high-quality results from large language models.
Reinforcement Learning for Trading Bots: Concepts and Pitfalls
Published: at 12:00 AMAn honest look at applying reinforcement learning to algorithmic trading — from environment design and reward shaping to the most common failure modes that sink RL trading projects.
Building a Sentiment Analysis Pipeline with Python
Published: at 12:00 AMA step-by-step guide to building a production-ready sentiment analysis pipeline in Python, from raw text cleaning to fine-tuning a transformer model and serving predictions via FastAPI.