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fastml vs moderndive

A side-by-side editorial comparison of fastml and moderndive — release velocity, themes, recent moves, and the top alternatives to consider.

fastml vs moderndive: at a glance

Featurefastmlmoderndive
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesautoml, tidymodels, survival analysis, cross-validationstatistics-education, webr, regression, r-package
Last editorial update55m ago4h ago
WebsiteVisit →Visit →

What is fastml?

fastml added survival modelling and leakage-proof resampling, moving past classification and regression.

A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.

Read the full fastml trajectory →

What is moderndive?

The ModernDive teaching package learns to render inside the browser that runs its own textbook

moderndive supplies the datasets, regression helpers and ggplot geoms used by the ModernDive introductory statistics textbook. Its release history is mostly dataset accumulation — much of it contributed by students in batches — punctuated by occasional function work. The latest release is different: it fixes View() so it renders inside webR, the in-browser R that powers the book's live exercises, and reworks the regression helpers to survive in-formula transformations.

Read the full moderndive trajectory →

fastml vs moderndive: editorial side-by-side

F
fastml
ANALYTICS
0.0

fastml added survival modelling and leakage-proof resampling, moving past classification and regression.

◆ Current state

A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.

◆ Where it's heading

The package is moving from convenience wrapper to something that has to be defensible statistically. Nested cross-validation, fold-wise rather than up-front imputation, and explicit leakage checks are all corrections to the shortcuts that make AutoML easy and its scores optimistic. Survival adds a third task type alongside classification and regression, and it arrived with its own metrics rather than being bolted onto the existing ones. Note the entry body is cut off at 8,000 characters, so the release is larger than what is shown.

◆ Prediction

Expect the remaining survival engines to fill in and the sandboxing of custom preprocessing to tighten, since both were still being iterated on within this same release's commit list.

M
moderndive
ANALYTICS
2.5

The ModernDive teaching package learns to render inside the browser that runs its own textbook

◆ Current state

moderndive supplies the datasets, regression helpers and ggplot geoms used by the ModernDive introductory statistics textbook. Its release history is mostly dataset accumulation — much of it contributed by students in batches — punctuated by occasional function work. The latest release is different: it fixes View() so it renders inside webR, the in-browser R that powers the book's live exercises, and reworks the regression helpers to survive in-formula transformations.

◆ Where it's heading

The package is following the textbook's second edition into the browser. webR has no pandoc, so the DT htmlwidget path the package relied on cannot produce the self-contained HTML the notebook cell needs, and the auto-print path was gated behind interactive() being false — meaning students working through the live exercises saw an explanatory message where a table should have been. Building a static HTML table and pushing it through webR's viewer hook is a small change with a direct effect on whether the book's interactive mode works at all.

◆ Prediction

With the book's v2 datasets landed and the browser rendering path fixed, the remaining friction is most likely in other functions that assume a desktop R session.

Alternatives to fastml and moderndive

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either fastml or moderndive.

See all fastml alternatives → · See all moderndive alternatives →

Recent activity from fastml and moderndive

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 12d agomoderndiveView() renders in webR; regression helpers survive formula transforms
  2. 8mo agofastmlVersion 0.7.5
  3. 1y agofastmlEngine-specific tuning, imbalance handling and explainability
  4. 1y agofastmlSingle-workflow evaluation fix
  5. 1y agofastmlVersion 0.5.0
  6. 1y agomoderndiveDatasets and tidy_summary() for the second edition
  7. 2y agomoderndiveAlmond and flight datasets for the inference chapters
  8. 4y agomoderndiveTen student-curated teaching datasets
  9. 4y agomoderndiveAlaska flights subset added
  10. 5y agomoderndiveCleaner regression tables and an explicit conf.level argument

Frequently asked questions

What is the difference between fastml and moderndive?

They serve adjacent needs but don't currently overlap on shipped themes. moderndive is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is fastml better than moderndive?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. moderndive is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to fastml?

Top fastml alternatives in Analytics are ranked by recent ship velocity. Browse the "fastml alternatives" section above for the current picks, or visit /alternatives/fastml for the full list with editorial commentary on each.

What are the best alternatives to moderndive?

Top moderndive alternatives in Analytics are ranked by recent ship velocity. Browse the "moderndive alternatives" section above for the current picks, or visit /alternatives/moderndive for the full list with editorial commentary on each.