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ML Libraries with a Bot: Software, Hardware and Parts

A 12-part series on using a bot with machine learning libraries: CUDA and driver checks, memory, pinning, PyTorch, TensorFlow, JAX, ONNX and more.

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House rules for this series: check every bot answer against the official docs we link, work in a virtual environment, load model files only from sources you trust, respect dataset and model licenses, and keep personal data out of bots and training sets. Every part labels what we tested ourselves and what is documented only.
Series complete. All 12 parts are published. The finale is Part 12: Review Your Training Code with a Bot: Checklist, which includes a recap of the whole series. Start with Part 1: GPU, Driver and CUDA Compatibility: A Bot-Assisted Check.

All 12 parts (12 of 12)

  1. Part 1GPU, Driver and CUDA Compatibility: A Bot-Assisted CheckGuide · Nov 3, 2026Part 1: collect your real driver, CUDA and library versions, then use a bot and NVIDIA's tables to check they fit before you install anything.
  2. Part 2How Much Memory Does a Model Need? A Data BriefData brief · Nov 3, 2026Part 2: estimate memory from parameter count and precision with a tested script, use Hugging Face's training figures, and let a bot sanity-check it.
  3. Part 3Pin Versions and Build Reproducible ML EnvironmentsWalkthrough · Nov 3, 2026Part 3: make a venv, pin exact versions with pip freeze, check with pip check, and see a real failed install that pinning would have caught.
  4. Part 4NumPy and pandas Basics with a Bot: Cheat SheetCheat sheet · Nov 3, 2026Part 4: shapes, dtypes, broadcasting, missing values and groupby, with real output from NumPy 2.5 and pandas 3.1, and prompts that keep a bot honest.
  5. Part 5Your First scikit-learn Model, Built with a BotWalkthrough · Nov 3, 2026Part 5: train and test a scikit-learn pipeline on the Iris dataset, with real accuracy and cross-validation output and a bot prompt that avoids leakage.
  6. Part 6PyTorch on the CPU: First Steps with a BotGuide · Nov 3, 2026Part 6: install a CPU-only PyTorch wheel, check it, and train a tiny model with a real loss curve, then ask a bot to explain each line.
  7. Part 7TensorFlow and Keras Install Requirements, ExplainedExplainer · Nov 3, 2026Part 7: what TensorFlow's pip page says about Python, platforms and GPUs, where it contradicts itself, and a real CPU check with Keras 3.
  8. Part 8JAX on the CPU: Field Notes with a BotField notes · Nov 3, 2026Part 8: install JAX for CPU, take a gradient, compile with jit and use explicit random keys, with real output and a hand-checked answer.
  9. Part 9Read Hugging Face Model Cards and Licenses with a BotGuide · Nov 3, 2026Part 9: check a model's license, gating, files and sizes from the Hub with a tested script before you download, and use a bot to read the card.
  10. Part 10Export a Model to ONNX and Run It: A Deep DiveDeep dive · Nov 3, 2026Part 10: convert a scikit-learn pipeline to ONNX, run it with ONNX Runtime, and prove the predictions match, with real output and GPU notes.
  11. Part 11Read ML Error Messages and Profile Code: Cheat SheetCheat sheet · Nov 3, 2026Part 11: four real PyTorch errors decoded, a cProfile run that finds the slow loop, and prompts that get a bot to fix the cause, not the symptom.
  12. Part 12Review Your Training Code with a Bot: ChecklistChecklist · Nov 3, 2026Part 12: a review checklist for ML training code, a real data-leakage example with a passing test, and a recap of the whole series.