Free-to-attend Artificial Intelligence (AI) weekend study group

Last week, we had a chat with Kevin about the new AI hub and other things, which was great. If you want to continue those topics, please come to join us.
This week, Peter is going to share a few things with us and Hollie would like to talk about random forest, which I am sure will be of interest to you.

After that, Stephen will show us how to get our hand dirty and do some simple coding with Keras.

Prerequirements:

(1) install anaconda
http://docs.anaconda.com/anaconda/install/windows/

(2) install Keras
https://anaconda.org/conda-forge/keras

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This free-to-attend Artificial Intelligence (AI) weekend study group is for both whom is from non-computer science background and those whom have already started in this field. The study group will go through materials used in universities like Stanford, Berkeley, and UCL. Covering cutting-edge techniques in AI and deep learning. It is targeted for people at different levels. The learning methods that we are going to follow are Richard Feynman’s technique and 1st principle. We believe everybody can be both learner and teacher. More importantly we would like to decompose complex codes line by line to make sure everybody understand what they are doing.

The first half of the whole course will last 9 weeks, after that learning will be through working on projects in a small group.

Course:
Course note: http://cs231n.stanford.edu/syllabus.html
Course video: https://www.youtube.com/playlist?list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk

Time and Location:
Time: arrive at 9:30, start at 10 am sharply every Saturday
Location: QUT D214 Garden Point

What we do together:

10:00 ~ 10:40 40 min Recap the course session video at high speed (1.5 ~2.o speed).
10:40 ~ 11:00 20 mins Q&A& discussion
11:00 ~ 12:30 70 mins working together on relevant code through Jupty notebook

To do list for yourself:

1. Install: Python 3.6 through Anaconda
   https://www.anaconda.com/download/

2. Reading:
   Python Numpy Tutorial http://cs231n.github.io/python-numpy-tutorial/
   Jupyter notebook Tutorial http://cs231n.github.io/ipython-tutorial/

3. Watching:
   https://www.youtube.com/playlist?list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk

4. Pick one or more Lectures from cs231n which you would like to teach.

5. Copy&paste the code of the lecture you picked into Jupty notebook line by line and try your best to teach others.

Learning Philosophy:

(We believe everybody can be both learner and teacher)

Freyman’s technical:

1. Choose a Concept
2. Teach it to a Toddler
3. Identify Gaps and Go Back to The Source Material
4. Review and Simplify (optional)
   1st principle:
   “the first basis from which a thing is known.”