mcminnra / notebooks

Repo of various notebooks I've written for data analysis, machine learning, AI, primers, and everything in-between

notebooks

Repo of various notebooks I've written to explore concepts, libraries, packages, and everything in-between.

If not written by me, source is attributed.

Deep Learning

Neural Network from Scratch - MNIST Dataset

Implements a neural network from scratch on the MNIST dataset. Also, Implements a few extras like DropConnect, ADAM Optimzation, and Generalization Loss Early Stopping

PyTorch Basic CNN

Basic CNN using the Dogs vs. Cats Dataset

Tensorflow Basic Feed-Forward NN - Iris Dataset

Basic Feed Forward / Multi_Layer Perceptron using Tensorflow and Iris Dataset.

Tensorflow Basic Feed-Forward NN (Best Practices) - Iris Dataset

Basic Feed Forward / Multi_Layer Perceptron using Tensorflow and Iris Dataset. Uses Tensorflow API best practices like layers and estimators

Tensorflow Basic CNN

Basic CNN using the Dogs vs. Cats Dataset

Tensorflow Neural Network

Basic Multi-Layer Perceptron using Tensorflow and MNIST dataset (Source)

Tensorflow Neural Network (Best Practices)

Basic Multi-Layer Perceptron using Tensorflow and MNIST dataset. Uses Tensorflow API best practices like layers and estimators (Source)

Interpretability

Frisch–Waugh–Lovell Theorem for Causality Estimation

Using Frisch–Waugh–Lovell Theorem for Causality Estimation of treatment variables

Skater Feature Importances

A notebook that looks are feature importances provided by the skater python package

Machine Learning

Bayesian Regression

Bayesian Regression using PyMC3

Collaborative Filtering

Explores user-to-user recommendation systems like similarity measures, Matrix Factorization, and how they are leveraged in Deep Learning.

Ensemble Stacking

Ensemble stacking example

Linear Regression

Linear Regression(s) from scratch

• Linear Regression
• Ridge Regression
• Polynomial Regression

Linear Regression - Closed Form vs. Gradient Descent

Compares Linear Regression's closed form solution against a gradient descent implementation

Logistic Regression

Logistic Regression from scratch

Optimization Python Libraries

Survey of optimization libraries in python. The notebook is mainly focused on hyperparameters, but you can use the libraries for any general optimization problem.

Softmax Regression

Softmax Regression (Multi-Class Logistic Regression) from scratch

Support Vector Machine

Support Vector Machine from scratch

Reinforcement Learning

Multi-Armed Bandits

Various MAB algorithms

Statistics

Beta Distribution

Overview of the Beta Distribution

Maximum Likelihood Estimation

MLE parameter estimation

Probability Distribution Intuitions

Intuitions and why you'd use them about highly used distributions

Probablistic Programming

Bayesian Parameter Estimation using pymc3