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Add the study notes, CausalML study and marketing decks to the library
Three team repositories had nothing in the library: the chapter notes for the book (15 pages on the team site), the CausalML study (4 decks, 5 notebooks) and Marketing Science (7 decks, in a new topic on marketing measurement). The library goes from 119 to 150 materials across 24 topics, and searches for MMM, attribution, Bayesian and CausalImpact now find something.
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‎assets/js/library.js‎

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["OCE-Materials", "온라인 실험 스터디", "온라인 통제 실험 스터디 발표"],
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["Experimentation-platform-materials", "실험 플랫폼 자료", "국내외 실험 플랫폼 사례 모음"],
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["causal-inference-practice", "산업 사례 템플릿", "기법별 산업 사례 발표"],
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["awesome-causal-inference-python", "메서드 코드북", "주제별 파이썬 코드"]
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["awesome-causal-inference-python", "메서드 코드북", "주제별 파이썬 코드"],
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["Smart_Causal_Inference", "책 스터디 노트", "『실무로 통하는 인과추론』 장별 정리"],
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["causal-inference-with-causalML", "CausalML 스터디", "책 이론을 causalml 코드로"],
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["Marketing_Science", "마케팅 사이언스", "마케팅 데이터와 베이지안 스터디 발표"]
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];
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const SRC_NAME = Object.fromEntries(SOURCES.map(([id, name]) => [id, name]));
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/* each material's curriculum level, so a newcomer can tell an intro from a research paper */

‎data/topics.json‎

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"repo": "causal-inference-practice",
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"title": "인과추론 Overview",
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"url": "https://github.com/CausalInferenceLab/causal-inference-practice/blob/main/Materials/Week02_Causal_inference_overview.pdf"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "1장 정리: 인과추론 소개",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter1.html"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "Frontdoor Criterion",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/examples/frontdoor_criterion.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "3장 정리: 그래프 인과모델",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter3.html"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "OLS",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/part1/ols.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "4장 정리: 유용한 선형회귀",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter4.html"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "Propensity Score & DML",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/part1/ipw_psm.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "5장 정리 (1): 성향점수 5.1–5.3",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter5_1.html"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "5장 정리 (2): 성향점수 5.4–끝",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter5_2.html"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "IV로 CATE 추정하기",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/part1/iv_cate.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "11장 정리 (1): 불응과 도구변수",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter11_1.html"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "11장 정리 (2): 도구변수 11.7–끝",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter11_2.html"
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},
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{
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"kind": "code",
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"repo": "causal-inference-with-causalML",
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"title": "도구변수: 선택 편향과 오차항",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/second%20half/4_%E1%84%83%E1%85%A9%E1%84%80%E1%85%AE%E1%84%87%E1%85%A7%E1%86%AB%E1%84%89%E1%85%AE.ipynb"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "Difference-in-Differences (DiD)",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/part1/did.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "8장 정리 (1): 이중차분법 8.1–8.3",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter8_1.html"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "8장 정리 (2): 이중차분법 8.4–8.8",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter8_2.html"
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},
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{
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"kind": "slides",
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"repo": "causal-inference-with-causalML",
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"title": "이중차분법 (10기 part 5)",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/%5B%EA%B0%80%EC%A7%9C%EC%97%B0%EA%B5%AC%EC%86%8C%5D%2010%EA%B8%B0%20part5%20%EC%9D%B4%EC%A4%91%EC%B0%A8%EB%B6%84%EB%B2%95.pdf"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "Synthetic Difference-in-Differences (SDID)",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/part1/sdid.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "9장 정리 (1): 표준 통제집단합성법",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter9_1.html"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "9장 정리 (2): 통제집단합성법",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter9_2.html"
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},
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{
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"kind": "slides",
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"repo": "causal-inference-with-causalML",
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"title": "통제집단합성법 (10기 part 7)",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/%5B%E1%84%80%E1%85%A1%E1%84%8D%E1%85%A1%E1%84%8B%E1%85%A7%E1%86%AB%E1%84%80%E1%85%AE%E1%84%89%E1%85%A9%5D%2010%E1%84%80%E1%85%B5%20part7%20%E1%84%90%E1%85%A9%E1%86%BC%E1%84%8C%E1%85%A6%E1%84%8C%E1%85%B5%E1%86%B8%E1%84%83%E1%85%A1%E1%86%AB%E1%84%92%E1%85%A1%E1%86%B8%E1%84%89%E1%85%A5%E1%86%BC%E1%84%87%E1%85%A5%E1%86%B8.pdf"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "신경망으로 CATE 추정하기",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/part2/cate_with_nn.ipynb"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "6장 정리: 이질적 처치효과",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter6.html"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "7장 정리: 메타러너",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter7.html"
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},
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{
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"kind": "slides",
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"repo": "causal-inference-with-causalML",
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"title": "이질적 처치효과 (10기 part 4)",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/%5B%EA%B0%80%EC%A7%9C%EC%97%B0%EA%B5%AC%EC%86%8C%5D%2010%EA%B8%B0%20part4%20%EC%9D%B4%EC%A7%88%EC%A0%81%20%EC%B2%98%EC%B9%98%ED%9A%A8%EA%B3%BC.pdf"
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},
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{
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"kind": "code",
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"repo": "causal-inference-with-causalML",
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"title": "메타러너 소개와 causalml 구현",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/second%20half/meta_learner_%EC%97%AC%ED%99%8D%EC%88%98.ipynb"
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},
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{
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"kind": "code",
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"repo": "causal-inference-with-causalML",
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"title": "DragonNet과 메타러너 비교",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/second%20half/DragonNet_meta_learner_comparison_%E1%84%87%E1%85%A1%E1%86%A8%E1%84%8B%E1%85%B5%E1%84%89%E1%85%A1%E1%86%A8.ipynb"
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},
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{
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"kind": "code",
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"repo": "causal-inference-with-causalML",
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"title": "CEVAE로 처치효과 추정",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/second%20half/3.CEVAE.ipynb"
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}
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]
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},
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"repo": "awesome-causal-inference-python",
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"title": "예산 제약 최적화",
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"url": "https://github.com/CausalInferenceLab/awesome-causal-inference-python/blob/main/book/examples/budget_constrained_optimization.ipynb"
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},
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{
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"kind": "code",
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"repo": "causal-inference-with-causalML",
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"title": "업리프트 트리",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/second%20half/2.%E1%84%8B%E1%85%A5%E1%86%B8%E1%84%85%E1%85%B5%E1%84%91%E1%85%B3%E1%84%90%E1%85%B3_%E1%84%90%E1%85%B3%E1%84%85%E1%85%B5_20250713.ipynb"
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}
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]
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},
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{
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"id": "marketing",
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"shelf": "causal",
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"name": "마케팅 효과 측정",
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"en": "Marketing Measurement",
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"about": "광고와 캠페인이 실제로 매출을 늘렸는지 따집니다. 베이지안 모델, 멀티터치 기여도, 준실험, 고객 생애 가치까지 마케팅 사이언스 스터디의 발표를 모았습니다.",
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"keys": [
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"마케팅",
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"광고 효과",
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"마케팅 효과",
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"기여도",
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"attribution",
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"MTA",
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"멀티터치",
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"MMM",
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"마케팅 믹스 모델",
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"증분",
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"incrementality",
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"베이지안",
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"Bayesian",
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"PyMC",
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"준실험",
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"CausalImpact",
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"Causal Impact",
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"고객 생애 가치",
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"CLV",
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"LTV",
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"RFM",
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"세그먼트"
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],
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"items": [
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "마케팅에서의 인과추론",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week03-%EB%A7%88%EC%BC%80%ED%8C%85%EC%97%90%EC%84%9C%EC%9D%98%20%EC%9D%B8%EA%B3%BC%EC%B6%94%EB%A1%A0.pdf"
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},
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "멀티터치 기여도와 MMM·증분 측정",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week06-Multi%20Touch%20Digital%20Attribution.pdf"
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},
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "준실험: 이중차분법, 합성통제, CausalImpact",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week07-%EC%A4%80%EC%8B%A4%ED%97%98%28Quasi-experiments%29.pdf"
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},
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "베이지안 다시 보기",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week02-Bayesian_Rethinking.pdf"
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},
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "PyMC와 시변 계수 모델 사례",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week05-PyMC%20%26%20TVC.pdf"
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},
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "고객 세분화와 RFM",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week08-Segmentation%20%26%20RFM.pdf"
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},
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{
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"kind": "slides",
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"repo": "Marketing_Science",
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"title": "PyMC-Marketing으로 고객 생애 가치 구하기",
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"url": "https://github.com/CausalInferenceLab/Marketing_Science/blob/main/PPT/%5BMarketing_Science%5D%20Week10-Customer%20Lifetime%20Value.pdf"
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}
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]
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},
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"repo": "causal-inference-practice",
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"title": "RCT와 실험 플랫폼",
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"url": "https://github.com/CausalInferenceLab/causal-inference-practice/blob/main/Materials/Week04_05_RCT_experiment_platform.pdf"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "2장 정리: 무작위 실험과 기초 통계",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter2.html"
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}
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]
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},
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"repo": "causal-inference-practice",
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"title": "스위치백 산업 사례",
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"url": "https://github.com/CausalInferenceLab/causal-inference-practice/blob/main/Materials/Week11_Switchback.pdf"
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},
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{
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"kind": "read",
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"repo": "Smart_Causal_Inference",
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"title": "10장 정리: 지역 실험과 스위치백 실험",
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"url": "https://causalinferencelab.github.io/Smart_Causal_Inference/docs/Chapter10.html"
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},
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{
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"kind": "slides",
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"repo": "causal-inference-with-causalML",
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"title": "대안적 실험 설계: 불응, 도구변수, 스위치백 (10기 part 5)",
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"url": "https://github.com/CausalInferenceLab/causal-inference-with-causalML/blob/main/Lecture%20Notes/%5B%EA%B0%80%EC%A7%9C%EC%97%B0%EA%B5%AC%EC%86%8C%5D%2010%EA%B8%B0%20Part%205.%EB%8C%80%EC%95%88%EC%A0%81%20%EC%8B%A4%ED%97%98%EC%84%A4%EA%B3%84.pdf"
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}
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]
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},

‎library.html‎

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<title>자료실 | Causal Inference Hub</title>
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<meta name="description" content="인과추론과 온라인 실험을 주제별로 공부할 수 있는 자료실입니다. 이중차분법, 성향점수, A/B 테스트, SRM, 분산 감소까지 가짜연구소 인과추론팀의 웹북·영상·코드·발표 자료와 용어집 183개를 한곳에 모았습니다.">
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<meta property="og:title" content="인과추론·온라인 실험 자료실 | Causal Inference Hub">
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