About our Club

http://www.freeknowledgemission.org/ 

We're located inside the North entrance of the Nike Victory/Edo Building in Air Zoom Blade Conference Room.

Come join us every Tuesday at the Tech Academy. This is an interactive and immersive instructor lead meeting. This week we will cover the basic foundations of neural networks, covering introduction to the perceptron, artificial neural networks (ANN), convolutional neural networks (CNN), recurrent neural networks (RNN), and wrap up with adversarial attacks on neural networks.

We use a digital project and whiteboard. The course is given at a comfortable pace, so that any attendee can interrupt and ask a question. No question is too small or wrong.

We ask all the attendees to be patient so that everyone attending learns at the same pace so that all attendees are at the same level at the end of the two hours.

• What we'll do
We'll be watching and working through Artificial Intelligence/Deep Learning classes as a group! There are excellent free course lectures and materials online, and from January 6th 2018 to April[masked] we'll go through all the contents.

In order to cater to a diverse audience, there will be 3 structured sessions every Saturday – you can attend all, some or none, it’s totally up to you! If you don’t want to attend some of the sessions, throughout the day there will be open hacking on creating open-source code implementations of the top research paper pre-prints that week. Or use that time to catch-up on lectures and readings (sessions 2 and 3 have many hardcore readings by the way!) while discussing with peers.

Session 1: Fast.ai i Part 1 (v2) Lesson 2
Session 2: Stat385 Lecture 3 Readings – Overview of Deep Learning
Session 3a: UCL/Deep Mind Reinforcement Learning Lecture 2 – Intro to Reinforcement Learning

Note that Sessions 1 & 2 will begin with the 2nd lecture of their corresponding courses.

The Agenda
Session 1
10:00 AM - 12:00 PM (Beginner-Intermediate)
Practical Deep Learning- Fast.ai Part 1 (v2)
http://forums.fast.ai/t/welcome-to-part-1-v2/5787

Break
12:00 PM - 1:00 PM Lunch
Occasional brown bag lunch talk from an expert :)

Session 2
1:00 PM - 3:00 PM (Intermediate-Advanced)
Deep Learning Theory- Stanford STAT385 course on Theories of Deep Learning
https://stats385.github.io/readings
https://stats385.github.io/lecture_slides
https://www.youtube.com/playlist?list=PLhWmdj1YUpdT-UwCLVRNX509hZrKqZ83V

Session 3 (Intermediate-Advanced)
3:00 PM - 6:00 PM
Reinforcement Learning- UCL/DeepMind Reinforcement Learning
https://www.youtube.com/playlist?list=PLacBNHqv7n9gp9cBMrA6oDbzz_8JqhSKo

This is the Portland, OR chapter of AI Saturdays https://nurture.ai/ai-saturdays

This will be a hands on Python and computer vision machine learning so bring a laptop. We will be doing code alongs in a Jupyter Notebook using the Gap NLP/CV Data Engineering framework for Machine Learning. The code along will focus on a variety of ways of using the framework to get images into machine language ready data, storage/retrieval, and mini-batch generation.

Gap is a new open source project in Portland in a pre-launch stage (v0.9 - alpha). For more information on Gap, see: https://github.com/andrewferlitsch/Gap