Blog
Developments in automated analysis, new software, research commentary and notes on where the field is going.
AI Development Services vs. Machine Learning Development Services: Key Differences and When to Use Each
AI development and ML development are not the same thing. AI builds systems from explicit rules; ML builds systems that learn from data. Choose AI when rules are known and stable. Choose ML when you have data and need prediction. Getting this wrong wastes budget and delivers wrong results.
How to Analyze Research Papers Faster with AI: A Data Scientist’s Workflow
AI can't replace reading the papers that matter, but it's an excellent filter for deciding which ones do. Here's my actual triage workflow.
M.Sc. in Data Science and Artificial Intelligence From BITS Pilani: The Complete 2026 Program Guide
BITS Pilani's M.Sc. in Data Science & AI is a 2-year online degree. Cost: INR 38,500/trimester (INR 2.31L total). DEB-approved. Includes 4 major projects and a professional portfolio. Best for working professionals seeking a recognised credential without career interruption.
F1 Score in Machine Learning: Formula, Range, and How to Interpret It
F1 score, precision, and recall: what they mean, when to use each, and why F1 beats accuracy on imbalanced classification problems.
Artificial Intelligence vs. Machine Learning vs. Data Science: What’s the Real Difference?
AI, ML, and data science get used interchangeably, but they're not the same thing. Here's the practical distinction that actually matters for hiring and scoping.
How AI Can Generate Statistical Reports
How generated statistical reports should be produced: from fitted structure to sentences, with checkable claims.
Python Plotting for Data Science: A Practical Introduction to Matplotlib
From messy CSV to publication-ready figure: a practical walkthrough of Python plotting for data science using matplotlib and pandas.
Bayesian Model Selection Explained
Bayesian model selection and the marginal likelihood: how complexity is penalised without an added penalty term.
Seaborn Color Palettes: A Practical Guide for Data Science in Python
Choosing the wrong Seaborn color palette can undermine a good chart. Here's a practical, code-first guide to sequential, diverging, and qualitative palettes.
Explainable AutoML vs Black-Box AutoML
The difference between AutoML that reports a structure and AutoML that reports a score, and when each is appropriate.