## 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 ...The buried assumption in constant dispersion tweedie models

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 ...Smoothing data with cubic spline approaches

more ...A matrix factorization approach to linear regression

more ...Generating correlated boostrap reserve estimates with R

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 special symbols in data.table

more ...Applications of inverse transform sampling

more ...Introduction to sqlite3 in Python

more ...Polynomial interpolation via Newton's method

more ...Sampling from mixed exponential distributions using the inverse transform method

more ...Using pip hehind a proxy

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

more ...Implementing custom binary operators in R

more ...Implementing variable argument functions in R

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 ...