{"id":27417861,"url":"https://github.com/chocochip101/tech-interview-study","last_synced_at":"2026-01-21T13:33:18.034Z","repository":{"id":88824974,"uuid":"429709032","full_name":"Chocochip101/Tech-Interview-Study","owner":"Chocochip101","description":"S.M, BoostCamp를 위한 기술 인터뷰 스터디","archived":false,"fork":false,"pushed_at":"2022-01-12T07:28:57.000Z","size":9321,"stargazers_count":0,"open_issues_count":2,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-14T09:59:39.925Z","etag":null,"topics":["algorithm","deep-learning","machine-learning"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Chocochip101.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-11-19T07:37:24.000Z","updated_at":"2021-11-30T11:51:26.000Z","dependencies_parsed_at":"2023-04-19T17:15:45.059Z","dependency_job_id":null,"html_url":"https://github.com/Chocochip101/Tech-Interview-Study","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Chocochip101/Tech-Interview-Study","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chocochip101%2FTech-Interview-Study","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chocochip101%2FTech-Interview-Study/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chocochip101%2FTech-Interview-Study/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chocochip101%2FTech-Interview-Study/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Chocochip101","download_url":"https://codeload.github.com/Chocochip101/Tech-Interview-Study/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Chocochip101%2FTech-Interview-Study/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28633763,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-21T04:47:28.174Z","status":"ssl_error","status_checked_at":"2026-01-21T04:47:22.943Z","response_time":86,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithm","deep-learning","machine-learning"],"created_at":"2025-04-14T09:57:02.594Z","updated_at":"2026-01-21T13:33:18.026Z","avatar_url":"https://github.com/Chocochip101.png","language":null,"readme":"# Tech Interview Study\n\n## 목차\n 1. [일정](#일정)\n 2. [참여](#참여)\n 3. [Contents](#Contents)\n 4. [공부자료](#공부자료)\n 5. [Answers](https://github.com/Chocochip101/ai-tech-interview/tree/main/answers)\n\n## 일정\n- [Day 1 (21.11.18)](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%201.pdf)\n- [Day 2 (21.11.21)](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%202.pdf)\n- [Day 3 (21.11.21)](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%203.pdf)\n- [Day 4 (21.11.25)](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%204.pdf)\n- [Day 5 (21.11.25)](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%205.pdf)\n- [Day 6 (21.11.25)](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%206.pdf)\n- [Day 7 (21.11.28)](https://github.com/Chocochip101/Tech-Interview-Study/blob/main/Contents/Day%207.pdf)\n- [Day 8 (21.11.28)](https://github.com/Chocochip101/Tech-Interview-Study/blob/main/Contents/Day%208.pdf)\n\n## 참여\n[Chocochip](https://github.com/Chocochip101) ([BLOG](https://chocochip101.tistory.com/)), [GardenJun](https://github.com/garden-jun)\n\n## Contents\n\n### [Day 1](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%201.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n\n- Statistic/Math\n1. 고유값(eigen value)와 고유벡터(eigen vector)에 대해 설명해주세요. 그리고 왜 중요할까요?\n2. 샘플링(Sampling)과 리샘플링(Resampling)에 대해 설명해주세요. 리샘플링은 무슨 장점이 있을까요?\n\n- Machine Learning\n3.정규화를 왜 해야할까요? 정규화의 방법은 무엇이 있나요?\n4. Local Minima와 Global Minima에 대해 설명해주세요.\n5. 차원의 저주에 대해 설명해주세요.\n\n- Deep Learning\n6. 딥러닝은 무엇인가요? 딥러닝과 머신러닝의 차이는?\n7. Cost Function과 Activation Function은 무엇인가요?\n8. Data Normalization은 무엇이고 왜 필요한가요?\n\n- Python\n9. What is the difference between list and tuples in Python?\n10. What are the key features of Python?\n  ---\n\u003c/details\u003e\n\n### [Day 2](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%202.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n- Statistic/Math\n1. 확률 모형과 확률 변수는 무엇일까요?\n2. 누적 분포 함수와 확률 밀도 함수는 무엇일까요? 수식과 함께 표현해주세요.\n\n- Machine Learning\n3. dimension reduction기법으로 보통 어떤 것들이 있나요?\n4. PCA는 차원 축소 기법이면서, 데이터 압축 기법이기도 하고, 노이즈 제거기법이기도 합니다. 왜 그런지 설명해주실 수 있나요?\n\n- Deep Learning\n5. 알고있는 Activation Function에 대해 알려주세요. (Sigmoid, ReLU, LeakyReLU, Tanh 등)\n6. 오버피팅일 경우 어떻게 대처해야 할까요?\n7. 하이퍼 파라미터는 무엇인가요?\n8. Weight Initialization 방법에 대해 말해주세요. 그리고 무엇을 많이 사용하나요?\n\n- Python\n9. What type of language is python? Programming or scripting?\n\n- Algorithm\n10. 다음 코드에서 print_all_prime_numbers 함수의 파라미터 N에 대한 시간 복잡도는 무엇일까요?\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/73146678/142587215-577b0016-bb90-4810-b0ca-d0bdaaaf4420.png\"  width=\"250\" height=\"350\"/\u003e\n\u003c/p\u003e\n  \n\n  ---\n\u003c/details\u003e\n\n### [Day 3](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%203.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n- Statistic/Math\n1. 조건부 확률은 무엇일까요?\n2. 공분산과 상관계수는 무엇일까요? 수식과 함께 표현해주세요.\n\n- Machine Learning\n3. LSA, LDA, SVD 등의 약자들이 어떤 뜻이고 서로 어떤 관계를 가지는지 설명할 수 있나요?\n4. Markov Chain을 고등학생에게 설명하려면 어떤 방식이 제일 좋을까요?\n\n- Deep Learning\n5. 볼츠만 머신은 무엇인가요?\n6. Tensorflow, PyTorch 특징과 차이가 뭘까요?\n7. TF, PyTorch 등을 사용할 때 디버깅 노하우는?\n8. 뉴럴넷의 가장 큰 단점은 무엇인가? 이를 위해 나온 One-Shot Learning은 무엇인가?\n\n- Python\n9. What is type conversion in Python?\n\n- Algorithm\n10. [Problem - BOJ 1914](https://www.acmicpc.net/problem/1914)\n\n  ---\n\u003c/details\u003e\n\n### [Day 4](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%204.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n\n- Statistic/Math\n1. 신뢰 구간의 정의는 무엇인가요?\n2. p-value를 모르는 사람에게 설명한다면 어떻게 설명하실 건가요?\n\n- Machine Learning\n3. 텍스트 더미에서 주제를 추출해야 합니다. 어떤 방식으로 접근해 나가시겠나요?\n4. SVM은 무엇이고 왜 반대로 차원을 확장시키는 방식으로 동작할까요? SVM은 왜 좋을까요?\n5. 다른 좋은 머신 러닝 대비, 오래된 기법인 나이브 베이즈(naive bayes)의 장점을 옹호해보세요.\n\n- Deep Learning\n6. 요즘 Sigmoid 보다 ReLU를 많이 쓰는데 그 이유는?\n7. ReLU로 어떻게 곡선 함수를 근사하나? ReLU의 문제점은?\n8. Bias는 왜 존재할까?\n\n- Python\n9. What is \\_\\_init__?\n\n- Algorithm\n10. [Problem - Programmers - 소수 찾기](https://programmers.co.kr/learn/courses/30/lessons/42839)\n  ---\n\u003c/details\u003e\n\n### [Day 5](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%205.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n\n- Statistic/Math\n1. R square의 의미는 무엇인가요?\n2. 평균(mean)과 중앙값(median)중에 어떤 케이스에서 뭐를 써야할까요?\n\n- Machine Learning\n3. 회귀 / 분류시 알맞은 metric은 무엇일까?\n4. Association Rule의 Support, Confidence, Lift에 대해 설명해주세요.\n5. 최적화 기법중 Newton’s Method와 Gradient Descent 방법에 대해 알고 있나요?\n\n- Deep Learning\n6. Gradient Descent에 대해서 쉽게 설명한다면?\n7. 왜 꼭 Gradient를 써야 할까? 그 그래프에서 가로축과 세로축 각각은 무엇인가? 실제 상황에서는 그 그래프가 어떻게 그려질까?\n8. GD 중에 때때로 Loss가 증가하는 이유는?\n9. Back Propagation에 대해서 쉽게 설명 한다면?\n\n- Python\n10. What is self in Python?\n\n- Algorithm\n11. 다음 코드의 출력 값은?   \n![image](https://user-images.githubusercontent.com/73146678/142759377-41d81415-36b4-4b1a-8bba-80957c225fab.png)\n  ---\n\u003c/details\u003e\n\n### [Day 6](https://github.com/Chocochip101/AI-Interview-Study/blob/main/Contents/Day%206.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n\n- Statistic/Math\n1. 중심극한정리는 왜 유용한걸까요?\n2. 엔트로피(entropy)에 대해 설명해주세요. 가능하면 Information Gain도요.\n\n- Machine Learning\n3. ROC 커브에 대해 설명해주실 수 있으신가요?\n4. K-means의 대표적 의미론적 단점은 무엇인가요? (계산량 많다는것 말고)\n5. 머신러닝(machine)적 접근방법과 통계(statistics)적 접근방법의 둘간에 차이에 대한 견해가 있나요?\n\n- Deep Learning\n6. GD가 Local Minima 문제를 피하는 방법과 찾은 해가 Global Minimum인지 아닌지 알 수 있는 방법은 무엇이 있을까요?\n7. Training 세트와 Test 세트를 분리하는 이유와 Validation 세트가 따로 있는 이유는?\n8. Test 세트가 오염되었다는 말의 뜻은 무엇인가?\n\n- Python\n9. What does *args, **kwargs mean? And why would we use it?\n\n- Algorithm\n10. [Problem - Programmers - 피로도](https://programmers.co.kr/learn/courses/30/lessons/87946)\n  ---\n\u003c/details\u003e\n\n### [Day 7](https://github.com/Chocochip101/Tech-Interview-Study/blob/main/Contents/Day%207.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n\n- Statistic/Math\n1. 어떨 때 모수적 방법론을 쓸 수 있고, 어떨 때 비모수적 방법론을 쓸 수 있나요?\n2. “likelihood”와 “probability”의 차이는 무엇일까요?\n\n- Machine Learning\n3. L1, L2 정규화에 대해 설명해주세요.\n4. Cross Validation은 무엇이고 어떻게 해야하나요?\n5. XGBoost을 아시나요? 왜 이 모델이 캐글에서 유명할까요?\n\n- Deep Learning\n6. Batch Normalization의 효과와 주의점은?\n7. GAN에서 Generator 쪽에도 BN을 적용해도 될까?\n8. CNN에 대해서 설명해주세요.\n9. Average Pooling과 Max Pooling의 차이점은?\n\n- Algorithm\n10. [Problem - Programmers - 교점에 별 만들기](https://programmers.co.kr/learn/courses/30/lessons/87377)\n  ---\n\u003c/details\u003e\n\n### [Day 8](https://github.com/Chocochip101/Tech-Interview-Study/blob/main/Contents/Day%208.pdf)\n\u003cdetails\u003e\n  \u003csummary\u003eContent\u003c/summary\u003e\n\n  ---\n\n- Statistic/Math\n1. 검정력(statistical power)은 무엇일까요?\n\n- Machine Learning\n2. 앙상블 방법엔 어떤 것들이 있나요?\n\n\n- Deep Learning\n3. 딥러닝 발달 이전에 사물을 Detect할 때 자주 사용하던 방법은 무엇인가요?\n4. Faster R-CNN의 장점과 단점은 무엇인가요?\n5. dlib은 무엇인가요?\n\n- Data Base\n6. Key란 무엇인가요?\n7. Key의 다섯 가지 종류에 대해 설명해주세요.\n\n- Algorithm\n8. [Problem - Programmers - 타켓 넘버](https://programmers.co.kr/learn/courses/30/lessons/43165)\n9. [Problem - Programmers - N으로 표현](https://programmers.co.kr/learn/courses/30/lessons/42895)\n\n  ---\n\u003c/details\u003e\n\n## 공부자료\n[BoostCamp AI Tech](https://github.com/Chocochip101/ai-tech-interview#-statisticsmath)  \n[DataScience Interview Questions](https://github.com/zzsza/Datascience-Interview-Questions)  \n[Tech Interview for Developer](https://github.com/gyoogle/tech-interview-for-developer)  \n[Interview Questions for Beginners](https://github.com/JaeYeopHan/Interview_Question_for_Beginner)  \n[Coding Test Problem Set](https://github.com/tony9402/baekjoon) ","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchocochip101%2Ftech-interview-study","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchocochip101%2Ftech-interview-study","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchocochip101%2Ftech-interview-study/lists"}