Blog
Developments in automated analysis, new software, research commentary and notes on where the field is going.
How to save a figure with a transparent background in Matplotlib (with Code)
Pass transparent=True to fig.savefig and choose a format such as PNG that supports an alpha channel.
How to share a colorbar across subplots in Matplotlib (with Code)
Give every subplot the same Normalize object and colormap, then pass the subplot axes to fig.colorbar.
How to create small-multiple scatterplots in Seaborn (with Code)
Use sns.relplot with kind="scatter" and col set to the grouping column to draw one scatterplot per group.
How to annotate heatmap values in Seaborn (with Code)
Set annot=True to print values inside Seaborn heatmap cells, and use fmt to control their display precision.
How to mask the upper triangle of a correlation heatmap in Seaborn (with Code)
Pass a Boolean upper-triangle mask to sns.heatmap; cells whose mask is True are hidden.
B.Tech in AI and Machine Learning from BITS Pilani WILP: The 2026 Complete Guide
BITS Pilani WILP B.Tech in AI & ML is a 4-year online degree for working professionals. Cost: ~INR 50–55K/semester (~INR 4–4.4L total). Best for professionals without a CS background who need a recognised undergraduate AI/ML credential for career transitions. Slower and more expensive than bootcamps but provides a degree.
Choropleth Mapping in Python: A Practical Guide to Geographic Data Science
The geometry is the easy part of a choropleth map. Classification is where most maps actually go wrong, here's how to get it right in Python.
Machine Learning in Logistics: Real Benefits, Use Cases, and Lessons from the Field
Demand forecasting, route optimization, predictive maintenance: five ways ML is used in logistics, and what actually determines success in practice.
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.
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.