## Gradient Descent for Logistic Regression

Implementing gradient descent in order to estimate logistic regression coefficients

more ...Implementing gradient descent in order to estimate logistic regression coefficients

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

more ...Gibbs sampling approaches for Bayesian linear regression

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

more ...A matrix factorization approach to linear regression

more ...Clustering in Python with k-Means

more ...Using the Haversine formula to compute geographic distances with examples

more ...Accessing C library functions from Python

more ...Developing command line applications with argparse and configparser

more ...Introduction to sqlite3 in Python

more ...Polynomial interpolation via Newton's method

more ...Using pip hehind a proxy

more ...Leveraging Pandas to read and write tables in an Oracle database

more ...Working with PDFs in PyPDF2

more ...Assessing the quality of machine learning classifiers with scikit-learn

more ...Implementing a Navie Bayes Classifier from scratch in Python

more ...Sharing data between processes with Python's multiprocessing library

more ...Estimating Logistic Regression Coefficents From Scratch in Python

more ...Assessing goodness-of-fit in Python with Scipy

more ...Kernel Density Estimation in Python

more ...Updating sample mean and variance to account for new observations without full recalculation

more ...Smoothed Empirical Percentile Matching with Python implementation

more ...Polynomial interpolation via Newton's divided differences

more ...A simple, effective PDF harvester in Python

more ...Using the Freedman-Diaconis Rule to determine optimal histogram bin width

more ...