Projects for Udacity's Machine Learning Engineer Nanodegree Program
This course teaches machine learning fundamentals and includes doing projects with real-world data.
Link for course here
The following projects were completed as part of this course:
- Titanic Survival Exploration: Exploring the 1912 Titanic dataset and using simple supervised learning algorithms to predict survival outcomes.
- Predict Boston Housing Prices: Using supervised learning algorithms (Regression) to predict the prices of houses in Boston.
- Finding Donors for CharityML: Using supervised learning algorithms (Classification) to create clusters of people who are most likely to donate to a fictitous charity called "CharityML".
- Creating Customer Segments: Using PCA and dimensionality reduction to describe the types of customers a wholesale distributor interacts with.
- Train a Smartcab to Drive: Using reinforcement learning algorithms (Q-learning) to teach a cab in a driving simulator how to navigate safely through traffic to a waypoint.
- Dog Breed Classifier: Use Deep Learning techniques (Convolutional Neural Networks) to build a dog breed classifier.
- Capstone Project: Use everything I learned to solve a problem of my choice. I decided to do a Kaggle competition titled "Personalized Medicine: Redefining Cancer Treament" where I applied machine learning techniques and neural networks to this natural language processing problem.