First of a series of machine learning workshops. Introduction to basic machine learning concepts and a non-math approach to Machine Learning. Build your first machine model using a Kaggle dataset! We will be covering basic concepts such as decision trees/forests, overfitting/underfitting, building the intuition behind how gradients are used for learning algorithms and hyper parameter tuning to help your model hit that sweet spot. We will be using guided Kaggle labs for the workshop and help you move closer to getting your first Kaggle certification! All you need is some basic python knowledge and a laptop.
Plus get some free snacks and beverages :)
(For U of T students only)