Graph Neural Networks – Theory, Architectures and Real-World Applications
📋 KEY INSIGHTSGraph Neural Networks (GNNs) extend deep learning to graph-structured data — networks of nodes and edges — enabling ML on social networks,...
Data Science Project Management – Agile, CRISP-DM and Delivering ML Projects
📋 KEY INSIGHTSThe most common reason data science projects fail is not technical — it is misalignment between what the team built and what...
NLP Applications – Sentiment Analysis, Named Entity Recognition and Text Classification
📋 KEY INSIGHTSNLP applications sit on a spectrum from rule-based to fully neural. For many production problems — email routing, basic intent classification, keyword...
Cloud Computing for Data Scientists – AWS, GCP and Azure Compared
📋 KEY INSIGHTSAWS, GCP, and Azure each hold approximately 30–33% of the cloud market, but they are not interchangeable for data science workloads —...
Data Science Interview Preparation – Complete 2026 Study Plan and Strategy
📋 KEY INSIGHTSData science interviews at top companies consist of five distinct round types — each testing a different competency. Failing to prepare separately...
