It's hard to avoid hearing about machine learning today. It seems that every business is making use, or in some cases misuse, of machine learning to improve how they do everything from hiring, to product design, to making it a feature in their products directly. Unfortunately, very few stories go past the surface layer of "this company / application uses machine learning". If you've heard those stories and are left wondering how they're applying machine learning, or what it is machine learning can even do, then two things are true:
- You're in good company
- You should attend this workshop
We'll cover the basics of machine learning. In particular, we'll look at:
- What kinds of problems can machine learning solve?
- Which algorithms are appropriate for a given problem?
- How do those algorithms work from a formal perspective?
- How do I evaluate and visualize the performance of a machine learning algorithm?
We'll do this by treating the workshop as a very condensed version of an ML course. We'll interleave labs and lectures throughout the day to give attendees a solid foundational understanding of machine learning techniques as well as some practical experience implementing and using the algorithms. Lab scaffolding code and examples will be provided in python, with reference implementations available after the conclusion of the workshop for self evaluation.
Attendees will leave with:
- A better understanding of what machine learning can and can't do
- A solid understanding of how to evaluate machine learning algorithms
- Familiarity with open source implementations of
- machine learning algorithms
- evaluation of ML algorithms
- visualization of data, ML algorithm performance