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[[TableOfContents]]
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== Overall Study Description ==
Study group to learn Machine Learning(ML) and Deep Learning.
Study group to learn Machine Learning(ML) and Deep Learning.
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== Plan ==
Book : '''"Jump to python."'''
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== Document ==
Google drive : https://drive.google.com/drive/folders/1Q-vzxWmzRtcfeHCWmD8gv8PUoddkrfOn?usp=sharing
[/References]
== Member ==
'''Kyeong Tae Kim (Study Leader)'''
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'''Sohyun Park'''
'''Junseok Lee'''
'''Youngseok Joo'''
== Sponsor ==
'''Junseok Lee'''
'''Youngseok Joo'''
'''Kim Hyeseong'''
'''Park Yesol'''
'''Lee Eunseo'''
'''Kim Hyomin'''
'''Park Yeonghyeon'''
'''Jeong Hyeon'''
'''Im Chanyeong'''
'''Choi Jaeyeong'''
== Sponsor ==
1. Overall Study Description ¶
Study group to learn Machine Learning(ML) and Deep Learning.
- from the ground up to the deep
- theory and practice in parallel
- assignment and flip learning.
- using book and video lecture.
flip learning : study at the home and then, share knowledge or exchange question in the meeting.
book : 0 : will be fixed.
video lecture : "Introduction to Deep Learning by Code" sponsored by SK Academy
2. Meeting Date ¶
2019 Winter Vacation
- Weekly Tuesday and Thursday.
- 2pm ~ 4pm
- 2pm ~ 4pm
2019 Term
- Weekly Wednesday.
- 8pm ~ 10pm (feat, end time is flexible)
- 8pm ~ 10pm (feat, end time is flexible)
3. Location ¶
Lecture room or project room with projector and white board.
Mainly in Building 208, 310 classroom.
We will be studying at a better facility over time.
4. How to join ¶
First come to "Zeropage Weekly Meeting(정모)".
Then, find "강제순", or Vice-President of ZeroPage, and tell him you wanting to join.
Or contact "김경태", or Study Leader, and tell him you wanting to join.
Kakao talk ID : kkt752
5. Requirement ¶
- with an Interest in ML and Deep Learning.
- with a strong responsibility.
- a person who will not give up easily.
- a person who will do properly // 하나를 하더라도 제대로, 확실하게 할 사람.
6. Plan ¶
1. First we study a programming language python, which is the most commonly used in data analysis.
Book : "Jump to python."
Video lecture : "Python for all, provided by edwith."
2. If we finish studying python, we will implement machine learning or deep learning using python.
Book : "Deep Learning from the Bottom"(will be.) or "machine learning using python library".
3. We will take a Coursera course, "Machine Learning, Andrew ng".
Book : "Jump to python."
Video lecture : "Python for all, provided by edwith."
Book : "Deep Learning from the Bottom"(will be.) or "machine learning using python library".
That is called ceremony of Machine Learning (ML의 정석).
-> Additional explanation will be written.4. If you do all of the above, we will go into advanced course.
we will study the TensorFlow, which is an library made for deep learning.
Book : "Golvin Hacker's 3-minute Deep Learning TensorFlow Flavor"
we will study the TensorFlow, which is an library made for deep learning.
Book : "Golvin Hacker's 3-minute Deep Learning TensorFlow Flavor"
&& "Tenserflow first step"
We will study them together. because one is a book which complement the other.
5. If we also acquire basis of TensorFlow, now it is time to take the famous lecture again.
Video lecture : Professor Kim Sung Hoon's 'Deep Learning for All' provided by YOUTUBE.
6. Video lecture : "Deep Learning learning from papers" provided by Edwith.
7. Video lecture : "Stanford CS231n" provided by YOUTUBE.
Video lecture : Professor Kim Sung Hoon's 'Deep Learning for All' provided by YOUTUBE.
This lecture is high-quality because it is shot and released annually into new 201x version.
8. It is stage to review all we learned.
Book : "hands on Machine Learning".
9. If we've come to this stage, there aren't lectures or books to be recommended.
It is stage to be a pioneer of deep learning, reading papers ourselves.
I wish us a good victory.
Good luck.
Book : "hands on Machine Learning".
It is stage to be a pioneer of deep learning, reading papers ourselves.
Good luck.
We need to discuss with our team members about assignment and penal system, ppt-uploading about study contents per week.
If above them is executed, we will upload files about them and proceed with the study writing these files.
8. Document ¶
Google drive : https://drive.google.com/drive/folders/1Q-vzxWmzRtcfeHCWmD8gv8PUoddkrfOn?usp=sharing
/References
/References
9. Member ¶
Kyeong Tae Kim (Study Leader)
Jesoon Kang (Vice-Leader)
Jisoo Kim
Sohyun Park
Junseok Lee
Youngseok Joo
Kim Hyeseong
Park Yesol
Lee Eunseo
Kim Hyomin
Park Yeonghyeon
Jeong Hyeon
Im Chanyeong
Choi Jaeyeong
Jesoon Kang (Vice-Leader)
Jisoo Kim
Sohyun Park
Junseok Lee
Youngseok Joo
Kim Hyeseong
Park Yesol
Lee Eunseo
Kim Hyomin
Park Yeonghyeon
Jeong Hyeon
Im Chanyeong
Choi Jaeyeong
