Difference between r1.18 and the current
@@ -1,5 +1,5 @@
강사: [김동영]
'''refer to'''
[https://cs231n.github.io/python-numpy-tutorial/ Python Numpy Tutorial]
새싹: [원지환], [이수은]
새싹: [원지환], ~~[이수은]~~
'''refer to'''
[https://cs231n.github.io/python-numpy-tutorial/ Python Numpy Tutorial]
@@ -7,18 +7,62 @@
'''calender'''
OT: 3/13
1차: 3/20
2차: 3/27
3차: 4/03
'''lecture material'''
[https://github.com/ktasha45/sprout-class-2022 github]
'''things to study'''
python
algorithm
3/20 20:00-20:45
참가: 김동영, 원지환
불참: 이수은 (알바 시간과 겹침)
불참: 이수은
배운 것
* python, jupyter notebook, colab 소개* boolean, 사칙연산, string, list, loop, dictionary
* [https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fraw.githubusercontent.com%2Fktasha45%2Fsprout-class-2022%2Fmaster%2Ffirst.pptx&wdOrigin=BROWSELINK ppt], [https://github.com/ktasha45/sprout-class-2022/blob/master/learn_python_1.ipynb colab]
다음 시간에 배울 것* class
* numpy
== 2차시 ==
3/27 21:00-21:50
배운 것
* numpy
* class 조금
* [https://github.com/ktasha45/sprout-class-2022/blob/master/learn_numpy.ipynb colab]
다음 시간에 배울 것
* numpy 실습
* matplotlib
== 3차시 ==
4/03 20:05-21:15
배운 것
* numpy
* matplotlib
* [https://github.com/ktasha45/sprout-class-2022/blob/master/learn_numpy2.ipynb colab]
실습
* numpy, matplotlib ([https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fraw.githubusercontent.com%2Fktasha45%2Fsprout-class-2022%2Fmaster%2Flearn_numpy2-quiz.pptx&wdOrigin=BROWSELINK quiz])
다음 시간에 배울 것
* Introduction of neural network
* Algorithm practice
== 4차시 ==
== 5차시 ==
5/01 20:00 - 21:10
배운 것
* tensroflow, keras
* perceptron, mlp
* [https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fraw.githubusercontent.com%2Fktasha45%2Fsprout-class-2022%2Fmaster%2F%25EC%2583%2588%25EC%258B%25B9%25EA%25B5%2590%25EC%258B%25A4%25205%25EC%25A3%25BC.pptx&wdOrigin=BROWSELINK ppt]
실습
* [https://colab.research.google.com/github/ktasha45/sprout-class-2022/blob/master/tensorflow_1.ipynb#scrollTo=cnN1ivXBpXhB NMIST 단순 신경망]
다음 시간에 배울 것
* CNN
* backpropagation
calender
OT: 3/13
1차: 3/20
2차: 3/27
3차: 4/03
OT: 3/13
1차: 3/20
2차: 3/27
3차: 4/03
things to study
python
algorithm
python
algorithm
