#visualisation

• 9 Aug 2024 · Paper summary

  Paper summary: Transformer Explainer: Learning LLM Transformers with Interactive Visual Explanation and Experimentation

  Transformer Explainer is an interactive, in-browser visual tool that runs a live GPT-2 so non-experts can follow a Transformer's data flow and watch next-token predictions change as they edit input and settings.

• 19 Apr 2024 · Study

  Matplotlib · Seaborn statistical plots

  Seaborn on top of Matplotlib: plots driven by DataFrame columns, hue for groups, and the statistical plots (box, violin, regression, heatmap).

• 16 Apr 2024 · Study

  Matplotlib · Styling

  Making plots readable: style sheets, colours, labels with units, annotations, removing chart junk, and saving at the right DPI.

• 10 Apr 2024 · Study

  Matplotlib · Subplots

  Grids of plots with plt.subplots, shared axes, uneven layouts with GridSpec / subplot_mosaic, and constrained layout.

• 4 Apr 2024 · Study

  Matplotlib · Line, bar, scatter and histogram

  The four plots I'll use most and when each fits: line for trends, bar for categories, scatter for relationships, histogram for distributions.

• 1 Apr 2024 · Study

  Matplotlib · Figure and Axes

  Matplotlib's object model: the Figure as the canvas and Axes as one plot, and why the explicit fig, ax = plt.subplots() style is clearer.