This month, Alyssa Batula will present on Machine Learning.
Her talk will cover:
1. What is machine learning?
2. What are features and labels, and how do you get them from your data?
3. How to use training and testing datasets
4. Supervised vs unsupervised learning
5. Classification vs regression
6. An overview of some commonly used classifiers
- Linear regression
- Nearest neighbors
- Support vector machines (time allowing)
- K-Means clustering (time allowing)
Resource for more information: