School of Computer Science Technical Workshop Series Presents: Applied Machine Learning with Python: By: Akram Vasighizaker

Friday, November 4, 2022 - 14:30 to 15:30

The School of Computer Science at the University of Windsor is pleased to present...

Technical Workshop Presentation by: Akram Vasighizaker- PhD Candidate

Applied Machine Learning with Python

Date: Friday, November 4th, 2022 

Time: 2:30 pm – 3:30 pm 

Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)

 

Abstract: 

In this workshop, which is separated into two sessions, we will begin with an intro to different platforms to apply machine learning tasks. Then, we will go through A-Z to play with data, including data exploring, slicing, and visualization using different packages in Python. Coding will perform on Goggle Colab, which is an online platform. There will be case study problems to start working on machine learning algorithms using scikit-learn. Microsoft Azure (and WEKA if we get time) are the other platforms which we will explore during the second session.

You will get access to the GitHub link of the workshop. At the end of this workshop, participants should:

  1. Be able to implement machine learning algorithms in practice.
  2. Be able to install and work with various Python packages
  3. Be able to work with various platforms to apply Machine/Deep Learning tasks

 

Prerequisites:

Acquaintance with Machin Learning concept.

Also, basic knowledge of programming is welcome

 

Workshop Outline:

Introduction

Working with Google Colab, Data Cleaning and Exploring, Data Visualization

Machine Learning with Scikit-Learn, Two-class Classification in Scikit-Learn (Case study: k-NN), Evaluation

Multiclass classification in Scikit-learn (Case study: Decision Tree), Grid search for Hyperparameter tuning

 

Biography: 

Akram is a PhD Candidate in Computer Science at the University of Windsor with research focuses mainly on Data representation Learning and Bioinformatics. Publishing high-quality papers in this field were the result of 4+ years of research in this field. Also, over 3 years of experience in the industry was a motivation to develop skills in other fields of data analysis, such as Business Intelligence.