Time-Series Forecasting: Beyond ARIMA
Transformers and probabilistic models for better forecasts.
Vision Transformers vs CNNs
Where each architecture shines in real-world vision apps.
Deploying Deep Learning on the Edge
Quantization and pruning tips to fit big models into tiny boxes.
RAG Systems: Retrieval that Actually Works
Practical chunking, indexing, and eval so your RAG doesn't hallucinate.
From Zero to Hero: Building Your First ML Pipeline
Walkthrough from raw data to deployment-ready model, step by step.
Prompt Engineering Playbook for Reliable LLMs
Patterns, guardrails, and evaluation techniques that keep outputs on target.
Interpretable ML in Healthcare
Transparency and fairness that clinicians can trust.
SQL for Data Scientists
Window functions, CTEs, and anti-joins you’ll reuses.