Long Short-Term Memory (LSTM) networks solve the limitations of traditional RNNs through a powerful gating mechanism. This article explains how the Forget, Input, and Output gates work internally, breaking down the math, vector dimensions, and intuition behind cell states and hidden states. A deep, implementation-level guide for serious deep learning practitioners.

Backpropagation is the core algorithm that trains neural networks by adjusting weights and biases to minimize error. This guide explains the intuition, math, chain rule, and real-world examples—making it easy to understand how neural networks actually learn.