## Gradient Descent for Logistic Regression

Implementing gradient descent in order to estimate logistic regression coefficients

## The Buried Assumption in Constant Dispersion Tweedie Models

The buried assumption in constant dispersion tweedie models

## Understanding the Graph Convolutional Network Propogation Model

Walking through the forward pass described in the Kipf and Welling paper

## Gibbs Sampling for Bayesian Linear Regression

Gibbs sampling approaches for Bayesian linear regression

## Using Dijkstra's Algorithm to Find All Shortest Paths in a Graph

Using Dijkstra's Algorithm to Find All Shortest Paths in a Graph

## Smoothing Data with Cubic Splines

Smoothing data with cubic spline approaches

## A Matrix Factorization Approach to Linear Regression

A matrix factorization approach to linear regression

## Generating Correlated Boostrap Reserve Estimates

Generating correlated boostrap reserve estimates with R

## Clustering in Python with k-Means

Clustering in Python with k-Means

## Calculating Distance Between Geographic Coordinate Pairs

Using the Haversine formula to compute geographic distances with examples

## Accessing C Library Functions from Python

Accessing C library functions from Python

## Developing Command Line Applications with argparse and configparser

Developing command line applications with argparse and configparser

## Introduction to Special Symbols in data.table

Introduction to special symbols in data.table

## Applications of Inverse Transform Sampling

Applications of inverse transform sampling

## Introduction to sqlite3

Introduction to sqlite3 in Python

## Polynomial Interpolation: Newton's Method

Polynomial interpolation via Newton's method

## Sampling from Mixed Exponential Distributions using the Inverse Transform Method

Sampling from mixed exponential distributions using the inverse transform method

## Using pip Behind a Proxy

Using pip hehind a proxy

## Interacting with Oracle from Pandas

Leveraging Pandas to read and write tables in an Oracle database

## User-Defined Binary Operators in R

Implementing custom binary operators in R

## Variable Argument Functions in R

Implementing variable argument functions in R

## Working with PDFs in PyPDF2

Working with PDFs in PyPDF2

## Evaluating Classifier Performance in scikit-learn

Assessing the quality of machine learning classifiers with scikit-learn

## Machine Learning Classification with Naive Bayes

Implementing a Navie Bayes Classifier from scratch in Python

## Shared Data Parallel Processing in Python

Sharing data between processes with Python's multiprocessing library