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Several notebooks embed YouTube videos as supplementary explanations. Most are foundational math from Khan Academy, MIT OCW (Strang), or 3Blue1Brown — pedagogically timeless and worth keeping. A handful, however, are old enough or off-topic enough that a refresh would help: dated software UIs or industry talks whose tooling landscape has moved on.
This issue tracks the audit and the refresh candidates. KEEP entries are listed at the bottom for reference; no action needed for those.
수치해법 노트북에 삽입된 YouTube 영상 중 일부는 화면이 오래되었으므로 새 영상으로 교체 후보를 정리.
Refresh candidates · 교체 후보
20_probability/30_pandas.ipynb (cell 166, right after a sns.pairplot example) — Wes McKinney Data science without borders (https://www.youtube.com/watch?v=wdmf1msbtVs, 2017). Industry/tooling perspective; the Arrow/pandas ecosystem has moved meaningfully since 2017. Either drop or replace with a more recent overview.
15_optimization/030_Classification_Optimization.ipynb — sigmoid (https://youtu.be/PIjno6paszY?t=650) and cross-entropy (https://youtu.be/6vzchGYEJBc) embeds. Source/upload metadata could not be confirmed during audit. ML pedagogy has improved a lot in the last few years (StatQuest, Andrej Karpathy zero-to-hero, 3Blue1Brown NN series) — strong replacement pool.
20_probability/15_random_variables.ipynb — Khan Academy How to create a histogram (https://www.youtube.com/watch?v=gSEYtAjuZ-Y). Elementary-grade level; statistics-track histogram explainers may be a better fit. Lower priority.
Not a refresh candidate · 교체 대상 아님
tutorial/05.jupyter_notebook.ipynb (cell 11) — Ray Dalio clip (https://youtu.be/xguam0TKMw8). Intentional: the surrounding cell illustrates Jupyter's flexibility to embed arbitrary media (videos, images, etc.). The specific clip is unrelated to numerical methods by design — it shows that the notebook can host any web content. Keep as-is.
KEEP — no action (audit record) · 유지 — 조치 불필요
Timeless / well-presented embeds confirmed during this audit
Khan Academy explanations are pedagogically canonical and resolution-independent; Strang's MIT 18.06 lectures are reference material; 3Blue1Brown's visualization quality stays evergreen.
Approach · 접근
Treat each checkbox as an independent PR — small, focused, easy to review. For each replacement, prefer (a) clearer pedagogy, (b) current UI/tooling where relevant, (c) Creative Commons / educational channels we already cite (Khan Academy, MIT OCW, 3Blue1Brown, StatQuest). If a strong replacement isn't found, removing the embed and strengthening the prose explanation is also acceptable.
Why · 이유
Several notebooks embed YouTube videos as supplementary explanations. Most are foundational math from Khan Academy, MIT OCW (Strang), or 3Blue1Brown — pedagogically timeless and worth keeping. A handful, however, are old enough or off-topic enough that a refresh would help: dated software UIs or industry talks whose tooling landscape has moved on.
This issue tracks the audit and the refresh candidates. KEEP entries are listed at the bottom for reference; no action needed for those.
수치해법 노트북에 삽입된 YouTube 영상 중 일부는 화면이 오래되었으므로 새 영상으로 교체 후보를 정리.
Refresh candidates · 교체 후보
20_probability/30_pandas.ipynb(cell 166, right after asns.pairplotexample) — Wes McKinney Data science without borders (https://www.youtube.com/watch?v=wdmf1msbtVs, 2017). Industry/tooling perspective; the Arrow/pandas ecosystem has moved meaningfully since 2017. Either drop or replace with a more recent overview.15_optimization/030_Classification_Optimization.ipynb— sigmoid (https://youtu.be/PIjno6paszY?t=650) and cross-entropy (https://youtu.be/6vzchGYEJBc) embeds. Source/upload metadata could not be confirmed during audit. ML pedagogy has improved a lot in the last few years (StatQuest, Andrej Karpathy zero-to-hero, 3Blue1Brown NN series) — strong replacement pool.tutorial/10.git.ipynb(cell 182) — Harvard CS50 EP. 4 git/GitHub lecture (https://www.youtube.com/watch?v=dAHgwd2U0Jg, 2018). UI elements (GitHub web, terminal output) are 7+ years old; modern git defaults (main,switch/restore) post-date the lecture. Coordinate with Pedagogy: refresh tutorial/10.git.ipynb (drop 2.23 hedges; add restore, SSH, default-branch=main, --rebase-merges) #418 which already refreshes the notebook's prose.tutorial/10.git.ipynb(cell 154) — sync-upstream playlist link (https://www.youtube.com/watch?v=P39pzSQx5rY&list=PLA6B0Lmr9oJNDafh3ndnmbXv0I9wddv63). Verify the playlist still resolves and is current; otherwise replace with a single up-to-date clip.20_probability/15_random_variables.ipynb— Khan Academy How to create a histogram (https://www.youtube.com/watch?v=gSEYtAjuZ-Y). Elementary-grade level; statistics-track histogram explainers may be a better fit. Lower priority.Not a refresh candidate · 교체 대상 아님
tutorial/05.jupyter_notebook.ipynb(cell 11) — Ray Dalio clip (https://youtu.be/xguam0TKMw8). Intentional: the surrounding cell illustrates Jupyter's flexibility to embed arbitrary media (videos, images, etc.). The specific clip is unrelated to numerical methods by design — it shows that the notebook can host any web content. Keep as-is.KEEP — no action (audit record) · 유지 — 조치 불필요
Timeless / well-presented embeds confirmed during this audit
00_introduction/50_pandas.ipynb20_probability/10_probability.ipynb20_probability/20_statistics.ipynb40_linear_algebra_1/10_vector_addition_subtraction.ipynb40_linear_algebra_1/20_vector_dot_cross_product.ipynb40_linear_algebra_1/40_matrix_and_vector.ipynb60_linear_algebra_2/100_Systems_of_Linear_Equations.ipynb60_linear_algebra_2/150_Inverse_matrix.ipynb60_linear_algebra_2/200_Eigenvalues_of_a_Matrix_PowerMethod.ipynb10_root_finding/45_newton_raphson_complex.ipynb30_num_int/10_first_order.ipynb50_ode/10_Forward_Euler.ipynb50_ode/55_Spread_of_disease.ipynbtutorial/10.git.ipynb(cell 183)Khan Academy explanations are pedagogically canonical and resolution-independent; Strang's MIT 18.06 lectures are reference material; 3Blue1Brown's visualization quality stays evergreen.
Approach · 접근
Treat each checkbox as an independent PR — small, focused, easy to review. For each replacement, prefer (a) clearer pedagogy, (b) current UI/tooling where relevant, (c) Creative Commons / educational channels we already cite (Khan Academy, MIT OCW, 3Blue1Brown, StatQuest). If a strong replacement isn't found, removing the embed and strengthening the prose explanation is also acceptable.