Repository for projects completed during the UC Berkeley Masters of Information and Data Science (MIDS) W07 course, "Applied Machine Learning"

class website: https://www.ischool.berkeley.edu/courses/datasci/261

This course provides a broad introduction to the key ideas in machine learning. The emphasis will be on intuition and practical examples rather than theoretical results, but utilizes theories in probability, statistics, and linear algebra will be important.

Projects in this repo indlude the following:

• Classifying emails as spam or authentic
• Classifying images of numerical digits as their corresponding number
• Use Gaussian Mixture Models to classify fungal features as a poisionous mushroom or safe to eat

Then my research team undertook the following kaggle project: https://www.kaggle.com/c/forest-cover-type-prediction