Machine Learning Fundamentals

Benjamin Fry

What Is This?

This folder is a collection of my efforts to apply what I have learned thus far on the topic of machine learning. The goal of doing this is to assemble a collection of models and applications of the models in order to utilize them in the future.

Contents

1. Perceptron / Linear Classifier - Perceptron.ipynb
2. Simple 3-Layer Neural Network Implementation and Non-Linear Classifier - Neural Network.ipynb
3. Application of Custom Neural Network Class to MNIST Data Set - MNIST Classifier.ipynb
4. Python Tensor Flow Classification Implementation on Titanic Data Set - Classification_TF.ipynb
5. Custom Linear Regression Model Implemented on Insurance Data Set - Linear_Regression.ipynb
6. Custom Locally Weighted Regression Model - Locally Weighted Regression.ipynb
7. Custom Logistic Regression Model - Logistic Regression.ipynb