455 CARDS · 41 WEEKS · EVERY SOURCE THE PLAN NAMES

Everything you could
study, filtered.

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.

Type Watch Read Run Track Biology AI & stats Build Craft Depth Core Optional Time ≤15 ≤30 ≤60 Week This week Clear all

5/16 Read 75 min W05 Thursday AI & stats

ISLP

ISLP ch. 6.1-6.2 (subset selection, ridge, lasso) and ch. 8 (trees, bagging, boosting) (75 min, skim the proofs)

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In: LABLOOP-W05 Notebook

4/12 Watch 75 min W06 Thursday AI & stats

Statistical Rethinking 2024

Statistical Rethinking 2024, lectures 1-2 (YouTube, from github.com/rmcelreath/stat_rethinking_2024) or Murphy, Probabilistic Machine Learning: An Introduction, ch. 2 — probml.github.io/pml-book/book1.html (75 min). Pick Rethinking if you want stories; Murphy if you want equations

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In: LABLOOP-W06 Notebook

4/12 Watch 75 min W07 Thursday AI & stats

Statistical Rethinking 2024

Statistical Rethinking 2024 lectures 3-4 (YouTube, 75 min)

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In: LABLOOP-W07 Notebook

4/15 Watch 120 min W08 Thursday AI & stats

Karpathy, "The spelled-out intro to neural networks and backpropagation: building micrograd"

Karpathy, "The spelled-out intro to neural networks and backpropagation: building micrograd" (YouTube, 2 h 25 min; watch the first 75 min Thursday, the rest Saturday while rewriting from memory)

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In: LABLOOP-W08 Notebook

2/10 Watch 120 min W09 Thursday AI & stats

Karpathy, "The spelled-out intro to language modeling: building makemore"

Karpathy, "The spelled-out intro to language modeling: building makemore" (YouTube, ~2 h; first 75 min Thursday)

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In: LABLOOP-W09 Notebook

3/11 Read 45 min W10 Thursday AI & stats

Rasmussen & Williams, Gaussian Processes for Machine Learning, ch. 1-2 — gaussianprocess.org/gpm…

Rasmussen & Williams, Gaussian Processes for Machine Learning, ch. 1-2 — gaussianprocess.org/gpml (free) (45 min) after Görtler, Kehlbeck & Deussen (2019), "A Visual Exploration of Gaussian Processes", Distill — distill.pub/2019/visual-exploration-gaussian-processes (30 min, interactive; start here)

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In: LABLOOP-W10 Notebook

4/12 Read 45 min W11 Thursday AI & stats

Agnihotri & Batra (2020), "Exploring Bayesian Optimization"

Agnihotri & Batra (2020), "Exploring Bayesian Optimization", Distill — distill.pub/2020/bayesian-optimization (30 min, interactive; start here); then Frazier (2018), "A Tutorial on Bayesian Optimization", arXiv:1807.02811, sections 1-4 (45 min)

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In: LABLOOP-W11 Notebook

4/12 Watch 40 min W12 Thursday AI & stats

Brunton & Kutz, Data-Driven Science and Engineering (2nd ed.), ch. 7 on SINDy — databookuw.com (…

Brunton & Kutz, Data-Driven Science and Engineering (2nd ed.), ch. 7 on SINDy — databookuw.com (free PDF) (40 min) + Steve Brunton "Sparse Identification of Nonlinear Dynamics (SINDy)" (YouTube, 30 min)

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In: LABLOOP-W12 Notebook

4/13 Read 30 min? W13 Thursday AI & stats

von Stosch et al. (2014), "Hybrid semi-parametric modeling in process systems engineering: past,…

von Stosch et al. (2014), "Hybrid semi-parametric modeling in process systems engineering: past, present and future", Computers & Chemical Engineering 60:86-101 (sections 1-3)

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In: LABLOOP-W13 Notebook

5/13 Read 30 min? W13 Thursday AI & stats

Chen et al. (2018), "Neural Ordinary Differential Equations"

Thursday · after von Stosch et al. (2014), "Hybrid semi-parametric modeling in process systems engineering: past,…

Chen et al. (2018), "Neural Ordinary Differential Equations", arXiv:1806.07366 (abstract + figure 1)

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In: LABLOOP-W13 Notebook

3/12 Watch 60 min W14 Thursday AI & stats

Stanford CS336 lecture on evaluation

Stanford CS336 lecture on evaluation (cs336.stanford.edu, videos on Stanford Online YouTube) (60 min); your week 7 notes on Zheng et al. 2023 judge biases (15 min)

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In: LABLOOP-W14 Notebook

2/10 Read 60 min W15 Thursday AI & stats

Jurafsky & Martin, Speech and Language Processing

Jurafsky & Martin, Speech and Language Processing (3rd ed. draft, web.stanford.edu/~jurafsky/slp3), chapter on information extraction (relation extraction and evaluation sections) (60 min); write the kappa paragraph into Methods

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In: LABLOOP-W15 Notebook

4/14 Read 60 min W16 Thursday AI & stats

Angelopoulos & Bates

Angelopoulos & Bates (2021), "A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification", arXiv:2107.07511, sections 1-2 (60 min)

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In: LABLOOP-W16 Notebook

3/13 Watch 40 min W17 Thursday AI & stats

Hugging Face model card facebook/esm2_t33_650M_UR50D

Hugging Face model card facebook/esm2_t33_650M_UR50D (10 min) + MIT 6.874 protein lecture second half (40 min); code block with ridge head

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In: LABLOOP-W17 Notebook

2/10 Watch 60 min W18 Thursday AI & stats

Simon Peyton Jones, "How to write a great research paper"

Simon Peyton Jones, "How to write a great research paper" (YouTube, Microsoft Research, ~1 h) + NeurIPS Paper Checklist (neurips.cc, current year's author guidelines) (30 min)

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In: LABLOOP-W18 Notebook

2/10 Run 40 min W19 Thursday AI & stats

Modern Statistics for Modern Biology sections on reporting and ISLP

Modern Statistics for Modern Biology sections on reporting and ISLP ch. 5.2 (bootstrap) re-read (40 min); apply bootstrap intervals across both papers

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In: LABLOOP-W19 Notebook

3/10 Read 75 min W20 Thursday AI & stats

P3 with the "staff ML scientist at a bioprocess company" persona; record a 10-minute explanation…

P3 with the "staff ML scientist at a bioprocess company" persona; record a 10-minute explanation of Paper 2 (75 min)

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In: LABLOOP-W20 Notebook