IEEE Ryerson Computer Chapter

Tutorial #1

Machine Learning Workshop #1
Date: Tuesday October 10, 2017
Presented by: Alice Rueda

In this first workshop, we cover the principals of k-means and assist you in setting up your laptops with the required program installation.
Anaconda Download Link: https://www.anaconda.com/download/#macos
Notes, Demo Python Code, and Matlab Machine Learning Readings: https://github.com/ieee-comp/ML_1
Event Page: Facebook Event Page

Tutorial #2

Machine Learning Applications Workshop #2
Date: Tuesday October 17, 2017
Presented by: Alice Rueda, Kirill Vas

Implementation of k-means in python. In this second workshop, we will implement the concepts covered in last weeks workshop.
Notes, Demo Code: https://github.com/ieee-comp/ML_2
Event Page: Facebook Event Page

Tutorial #3

Machine Learning Workshop #3
Date: Friday October 27, 2017
Presented by: Alice Rueda

Join us for the first research oriented session of our Machine Learning workshop series. The topic for this session is Markov Chain Monte Carlo for parameter estimation.
Notes:
Event Page: Facebook Event Page

Tutorial #4

Machine Learning Workshop #4
Date: Tuesday October 31, 2017
Presented by: Michael Zara

This session will be a review of workshop #2 and will focus more on the implementation of K-means in Python. Remember to bring your laptops as you will be getting coding exercises.
Agenda:
1) General description of unsupervised learning methods with an emphasis on k-means and its applications
2) Basic syntax (conditional statements, for loops, while loops, storing/taking values from matrices and vectors)
3) Walk through pseudo code/flowchart
Notes, Demo Code: https://github.com/ieee-comp/ML_4
Event Page: Facebook Event Page

Tutorial #5

SQL Workshop Series In Collaboration with RECESS #1
Date: Monday November 6, 2017
Presented by: Sean Gorsky

SQL is a programming language, more specifically, a query language primarily used to retrieve information and manipulate data from databases.
Why is it in high-demand?
All companies, in almost any industry, rely on data and need to organize and understand the information in a relevant way, due to which they are always in need of hiring someone with knowledge in databases!
Download Postgre: https://www.postgresql.org/download/
Event Page: Facebook Event Page
Notes, Demo Code: https://github.com/ieee-comp/SQL_ws_1

Tutorial #6

Machine Learning Workshop #5
Date: Tuesday November 7, 2017
Presented by: Alice Rueda

Brief overview of KNN. Brief overview of Big Data and Data Analytics
Notes, Demo Code: https://github.com/ieee-comp/ML_5

Tutorial #7

Machine Learning Workshop #6
Date: Friday November 10, 2017
Presented by: Alice Rueda

This Felipe's description: Since they first showed up, in imaging processing, attention mechanism have proven to be quite useful. In the last years, they have been used for NLP problems like translation.
In the first part, we introduced attention mechanisms at a general level (This first part is quite introductory and should be accessible to anybody)
In the second part (given we have enough time), I will explain how to produce a simple attention mechanism in Tensorflow, talk about the different types of attention, and what are the potential bottlenecks on building the models. We will also go over a simple example.
If there's still time, we will talk about Tensor2Tensor.
Notes: Demo Code: https://github.com/ieee-comp/ML_6