Summary

A 4 hour workshop on practical skills in machine learning prediction beginning with regression analysis and progressing to different machine learning techniques including clustering analysis, text mining, natural language processing and a quick demo of a simple neural network. A basic understanding of R and statistics is recommended (see Part I and Part II of Introduction to Data Science Series). Each topic will be covered with an overview and then hands on practice.

Audience:

This is ideal for people who have a basic understanding of math, statistics and R programming with a strong willingness to learn and practice! A laptop is required to attend the session! Ideally, you would have taken our part Part I and II workshop.

Goal:

You will finish the day with the fundamental knowledge of what people mean when they say machine learning and predictive analytics. You will gain a few new tools in your toolset when it comes to dealing with, understanding, and analyzing data. You will definitely have fun, meet new friends and would have learned many things about the exciting world of Analytics!

Breakdown of Schedule:

• Introduction to concepts in Machine Learning and demo of neural networks
• Regression analysis in machine learning context
• Clustering analysis in R
• Natural Language processing mini primer
• Text mining and word clouds in R

About the instructor:

Eric has an undergraduate degree in HBA from Ivey Business School, a Honors Specialization in Economics from Western University and a Masters of Science in Analytics from Ivey Business School. He worked in various capacities in consulting, business development, finance, and academia and has experiences teaching undergraduate and masters level students in fun, engaging and practical ways. You can check out his experiences here!

He's also a totally fun and friendly individual who loves to learn about everything in the world. Also an avid coffee drinker, and volunteer.

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