455 CARDS · 41 WEEKS · EVERY SOURCE THE PLAN NAMES
Every video, chapter, paper and repository in the programme, as one card each, with the time it costs and why it is there. Filter by how long you have.
15 cards shown. Stashes: LABLOOP-W00 Notebook (15) LABLOOP-W01 Notebook (18) LABLOOP-W02 Notebook (15) LABLOOP-W03 Notebook (19) LABLOOP-W04 Notebook (17) LABLOOP-W05 Notebook (16) LABLOOP-W06 Notebook (12) LABLOOP-W07 Notebook (12) LABLOOP-W08 Notebook (15) LABLOOP-W09 Notebook (10) LABLOOP-W10 Notebook (11) LABLOOP-W11 Notebook (12) LABLOOP-W12 Notebook (12) LABLOOP-W13 Notebook (13) LABLOOP-W14 Notebook (12) LABLOOP-W15 Notebook (10) LABLOOP-W16 Notebook (14) LABLOOP-W17 Notebook (13) LABLOOP-W18 Notebook (10) LABLOOP-W19 Notebook (10) LABLOOP-W20 Notebook (10) LABLOOP-W21 Notebook (13) LABLOOP-W22 Notebook (10) LABLOOP-W23 Notebook (9) LABLOOP-W24 Notebook (9) LABLOOP-W25 Notebook (12) LABLOOP-W26 Notebook (11) LABLOOP-W27 Notebook (10) LABLOOP-W28 Notebook (6) LABLOOP-W29 Notebook (7) LABLOOP-W30 Notebook (10) LABLOOP-W31 Notebook (8) LABLOOP-W32 Notebook (5) LABLOOP-W33 Notebook (13) LABLOOP-W34 Notebook (12) LABLOOP-W35 Notebook (10) LABLOOP-W36 Notebook (8) LABLOOP-W37 Notebook (7) LABLOOP-W38 Notebook (6) LABLOOP-W39 Notebook (6) LABLOOP-W40 Notebook (6)
Saturday sandbox
Good enough practices in scientific computing, Wilson et al., PLoS Computational Biology 2017. The repo habits you are setting up today, justified
In: LABLOOP-W00 Notebook
Saturday sandbox · after Elliot Hershberg, Century of Biology newsletter
carpentries-lab/good-enough-practices — the lesson version of R3, if you would rather do it than read it
In: LABLOOP-W00 Notebook
Saturday sandbox · after Steve Brunton
Deisenroth, Faisal & Ong, Mathematics for Machine Learning, ch. 10 "Dimensionality Reduction with PCA" — free PDF at mml-book.github.io
In: LABLOOP-W02 Notebook
Saturday sandbox · after Stanford Online · Statistical Learning with Python
Nomikos P. & MacGregor J.F., "Multivariate SPC Charts for Monitoring Batch Processes", Technometrics 37(1):41-59, 1995. DOI 10.1080/00401706.1995.10485888 · author PDF mirror: three-mode.leidenuniv.nl/pdf/n/nomikosmacgregor1995tmet.pdf. The founding paper of batch MSPC — abstract and figures are enough. Cite it in week 08's report
In: LABLOOP-W03 Notebook
Saturday sandbox · after Kourti T. & MacGregor J.F., "Process analysis, monitoring and diagnosis, using multivariate proj…
salvadorgarciamunoz/pyphi — a pharma practitioner's PCA/PLS with T² and SPE. Niche, but written by someone who does this for a living
In: LABLOOP-W03 Notebook
Saturday sandbox · after The Turing Way — book.the-turing-way.org, chapters on "Version control"
carpentries-lab/good-enough-practices — the hands-on lesson behind week 00's R3
In: LABLOOP-W04 Notebook
Saturday sandbox · after carpentries-lab/good-enough-practices
Zenodo help — versioning and GitHub integration, if the DOI badge misbehaves
In: LABLOOP-W04 Notebook
Saturday sandbox · after 3Blue1Brown "Bayes theorem, the geometry of changing beliefs"
STRENDA guidelines (Standards for Reporting Enzymology Data) — search "STRENDA guidelines" (verify URL). A real "minimum information" standard; it shows what a reporting checklist looks like and will inspire your completeness analysis
In: LABLOOP-W06 Notebook
Saturday sandbox
Anthropic Claude Cookbooks (github.com/anthropics/claude-cookbooks) — "extracting structured JSON" and "tool use" recipes
In: LABLOOP-W07 Notebook
Saturday sandbox · after 3Blue1Brown Neural Networks ch. 3-4 ("Backpropagation, intuitively"
Stanford CS231n notes "Backpropagation, intuitions" (cs231n.github.io/optimization-2) — a classic written explanation
In: LABLOOP-W08 Notebook
Saturday sandbox · after Notin et al. (2023), "ProteinGym: large-scale benchmarks for protein fitness prediction and desi…
Andrew White, Deep Learning for Molecules and Materials — dmol.pub, chapter on "Deep learning on sequences" (with Colab buttons)
In: LABLOOP-W17 Notebook
Saturday sandbox
Michael Clark, Mixed Models with R — m-clark.github.io/mixed-models-with-R (concepts transfer to Python)
In: LABLOOP-W25 Notebook
Saturday sandbox · after Michael Clark, Mixed Models with R
Bambi documentation (bambinos.github.io/bambi), Bayesian mixed models in one formula
In: LABLOOP-W25 Notebook
Saturday sandbox
Vaux, Fidler & Cumming (2012), "Replicates and repeats—what is the difference and is it significant?", EMBO Reports 13:291-296
In: LABLOOP-W30 Notebook
Saturday sandbox · after NIST Privacy Framework overview
Stanford HAI AI Index report, chapter on responsible AI (for context in M5)
In: LABLOOP-W35 Notebook