2019년 3월 25일
2019년 1학기 Python MOOC 수강자들에게 알립니다. 4주차 강의를 수강한 후 아래 숙제를 제출기한에 맞춰 제출해주시기 바랍니다. #### Lab #4 1) 링크 - https://github.com/TeamLab/Gachon_CS50_Python_KMOOC/tree/master/lab_assignment/lab_4 2) 참고영상 - https://youtu.be/5niJ5yiAlSQ?list=PLBHVuYlKEkUJvRVv9_je9j3BpHwGHSZHz 3) 제출기한 - 4월 5일(금) 17시 30분까지 4) 제출방법 - Gachon Autograder를 사용하여 theTeamLab.io를 통해 제출
2019년 3월 21일
[ML 3주차](https://github.com/TEAMLAB-Lecture/ml-101/tree/master/2019)의 Numpy 강의를 보시고 세 번째 숙제인 `Numpy` Lab을 수행하시기 바랍니다. - 숙제 설명: https://github.com/TEAMLAB-Lecture/ml-101/tree/master/2019/lab_asssigment/1_lab_numpy - 제출날짜: AI대학원(4월 13일 13:00), 학부데이터과학과정(4월 3일 12:00) ## 강의영상 ### Chapter 3 - Numpy Section #### Lecture - Chapter Intro - [강의영상](https://www.youtube.com/watch?v=NIWYNg8Gh70&index=14&t=0s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl), [강의자료](https://1drv.ms/b/s!ApZ4mg7k2qYhgaNyqXoFReKxEoauMA), [강의코드](https://github.com/TeamLab/machine_learning_from_scratch_with_python/tree/master/code/ch3), [코드다운로드](https://s3.ap-northeast-2.amazonaws.com/teamlab-gachon/mooc_pic/ml_ch3.zip) - Numpy overview - [강의영상](https://www.youtube.com/watch?v=aHthqCgsSFs&index=15&t=80s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - ndarray - [강의영상](https://www.youtube.com/watch?v=0uNh9qrFUJE&index=16&t=15s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Handling shape - [강의영상](https://www.youtube.com/watch?v=yHD1ApkUWRQ&index=17&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Indexing & Slicing - [강의영상](https://www.youtube.com/watch?v=1sH_HrRirbY&index=18&t=76s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Creation functions - [강의영상](https://www.youtube.com/watch?v=GcP0uvZCgZM&index=19&t=4s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Opertaion functions - [강의영상](https://www.youtube.com/watch?v=H6wx5PEkwoA&index=20&t=39s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Array operations - [강의영상](https://www.youtube.com/watch?v=whtNpVWYLIo&index=21&t=0s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Comparisons - [강의영상](https://www.youtube.com/watch?v=TdVSKlgvdkA&index=22&t=27s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Boolean & fancy Index - [강의영상](https://www.youtube.com/watch?v=A2BT1sWKaUE&index=23&t=1s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) - Numpy data i/o - [강의영상](https://www.youtube.com/watch?v=N4KjOIs-2H8&index=24&t=51s&list=PLBHVuYlKEkUKnfbWvRCrwSuSeYh_QUlRl) #### Supplements - TF-KR 첫 모임: Zen of NumPy - [발표자료](https://speakerdeck.com/shurain/zen-of-numpy), [강의영상](https://www.youtube.com/watch?v=Dm2wkObQSas&index=2&list=PLlMkM4tgfjnIMPagE47noYAJ222zWc4rw) (하성주, 2016)
2019년 3월 19일
2019년 1학기 Python MOOC 수강자들에게 알립니다. 3주차 강의를 수강한 후 아래 숙제를 제출기한에 맞춰 제출해주시기 바랍니다. #### Lab #3 1) 링크 - https://github.com/TeamLab/Gachon_CS50_Python_KMOOC/tree/master/lab_assignment/lab_3 2) 참고영상 - https://youtu.be/TIrSDV7JZ2E?list=PLBHVuYlKEkUJvRVv9_je9j3BpHwGHSZHz 3) 제출기한 - 3월 29일(금) 17시 30분까지 4) 제출방법 - Gachon Autograder를 사용하여 theTeamLab.io를 통해 제출
2019년 3월 19일
This is the announcement for the first lab assignments of our class. Check the following descriptions and submit your lab assignments. I think you may have a big problem to submit your assignments on the server. To help all of you, we will open TA session upcoming Thursday(3/21) 17:30 at Engineering Building 503. I really recommend you to join the session with your laptop. #### Lab #1 1) Descrition link - https://github.com/TEAMLAB-Lecture/python-mooc-english/tree/master/lab_assignment/lab_1 2) Videos(in Korean) - https://youtu.be/Qoid8G49zHI 3) Due date - until March 29, 17:30 4) Submssion method - Gachon Autograder #### Lab #2 1) Descrition link - https://github.com/TEAMLAB-Lecture/python-mooc-english/tree/master/lab_assignment/lab_2 2) Videos(in Korean) - https://youtu.be/uWDvBHv-icQ?list=PLBHVuYlKEkUJvRVv9_je9j3BpHwGHSZHz 3) Due date - until March 29, 17:30 4) Submssion method - Gachon Autograder
2019년 3월 15일
Hello, guys! This is a syllabus for our class until week 2. Please, check the contents and watch the lecture videos. Next Monday, we announce your assignments and we also update the quizzes for week 1 and 2 on Wednesday. We recommend you watch reference videos from PY4E which is a world popular lecture for Python. You can use the computer room at Gachon 712. I think we will have an offline TA session next Wednesday for your assignments. See you. Course website - [https://github.com/TEAMLAB-Lecture/python-mooc-english](https://github.com/TEAMLAB-Lecture/python-mooc-english)
2019년 3월 14일
[ML 2주차](https://github.com/TEAMLAB-Lecture/ml-101/tree/master/2019)의 Supplements 강의를 보시고 두 번째 숙제인 `Linear Algebra` Lab을 수행하시기 바랍니다. - 숙제 설명: https://github.com/TEAMLAB-Lecture/ml-101/tree/master/2019/lab_asssigment/0_linear_algebra - 제출날짜: AI대학원(3월 23일 13:00), 학부데이터과학과정(3월 20일 12:00) ## 강의영상 #### Supplements - Linear algebra - [주차강의자료](https://1drv.ms/b/s!ApZ4mg7k2qYhgaM5mMaDdd-dLeHGRg), [강의코드](https://github.com/TeamLab/introduction_to_python_TEAMLAB_MOOC/raw/master/code/week_9_code.zip) - List comprehension - [강의영상](https://www.youtube.com/watch?v=x09kQZ7AoL4) - Map & Reduce - [강의영상](https://www.youtube.com/watch?v=locakgld0iI&list=PLBHVuYlKEkUJcXrgVu-bFx-One095BJ8I&index=61&t=0s), [강의자료](https://1drv.ms/b/s!ApZ4mg7k2qYhgaMlP65yXLT9nBgcIw) - Asterisk - [강의영상](https://www.youtube.com/watch?v=dC_pUe78RMw&list=PLBHVuYlKEkUJcXrgVu-bFx-One095BJ8I&index=62&t=0s), [강의자료](https://1drv.ms/b/s!ApZ4mg7k2qYhgaMoM3jaeXaYfhNFAg) - Lab: Simple Linear algebra concepts- [강의영상](https://www.youtube.com/watch?v=zHQADUWi1pU&list=PLBHVuYlKEkUJcXrgVu-bFx-One095BJ8I&index=63&t=0s), [강의자료](https://1drv.ms/b/s!ApZ4mg7k2qYhgaMuKaE5x8t0z1Z4vw) - Lab: Simple Linear algebra codes - [강의영상](https://www.youtube.com/watch?v=T_axlKMne-0&list=PLBHVuYlKEkUJcXrgVu-bFx-One095BJ8I&index=64&t=0s), [강의자료](https://1drv.ms/b/s!ApZ4mg7k2qYhgaMv7umjL_JYHsubsA) ## Assignment: Linear algebra with pythonic code - [숙제설명](./lab_asssigment/0_linear_algebra) - [숙제파일](https://github.com/TEAMLAB-Lecture/ml-101/raw/master/2019/lab_asssigment/0_linear_algebra/ps_1.zip) - [강의영상](https://www.youtube.com/watch?v=6g5k-gCT1Lk&t=9s&index=65&list=PLBHVuYlKEkUJcXrgVu-bFx-One095BJ8I)
2019년 3월 12일
2019년 1학기 Python MOOC 수강자들에게 알립니다. 아래의 두개의 숙제를 제출기한에 맞춰 제출해주시기 바랍니다. #### Lab #1 1) 링크 - https://github.com/TeamLab/Gachon_CS50_Python_KMOOC/tree/master/lab_assignment/lab_1 2) 참고영상 - https://youtu.be/Qoid8G49zHI 3) 제출기한 - 3월 22일(금) 17시 30분까지 4) 제출방법 - Gachon Autograder를 사용하여 theTeamLab.io를 통해 제출 #### Lab #2 1) 링크 - https://github.com/TeamLab/Gachon_CS50_Python_KMOOC/tree/master/lab_assignment/lab_2 2) 참고영상 - https://youtu.be/uWDvBHv-icQ 3) 제출기한 - 3월 22일(금) 17시 30분까지 4) 제출방법 - Gachon Autograder를 사용하여 theTeamLab.io를 통해 제출
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