Leveraging network motifs to improve artificial neural networks

A hands‑on, first‑principles guide to fitting logistic regression via the Iteratively Reweighted Least Squares (IRLS) algorithm complete with mathematical derivations, R code from scratch, and a real‑world S&P data case study to bring your statistical modeling skills to the next level.

A lightweight C++ tool that prices European call and put options using the Black–Scholes formula, computes all key Greeks (Δ, Γ, Θ, Vega, Rho), and lets you run quick ATM/ITM/OTM scenario checks—all via a simple command‑line interface.

This MATLAB function efficiently computes the inverse of a square matrix using LU factorization. By decomposing the matrix into lower and upper triangular matrices, the function solves for the inverse with improved numerical stability.

StableStockPredictor is a robust deep learning model for predicting S&P 500 stock prices, built with TensorFlow and Keras. It leverages LSTM networks with gradient clipping, robust scaling, and stable feature engineering (e.g., RSI, moving averages, volatility) to ensure reliable performance in volatile markets.