Energy-Based Models (EBMs) are a family of generative (and sometimes discriminative) models that assign a scalar energy to each possible data point. Intuitively, EBMs learn to give low energy to
Category: TECH
Simpson’s Paradox: When Aggregated Data Tells the Wrong StorySimpson’s Paradox: When Aggregated Data Tells the Wrong Story
In data analysis, it is tempting to trust the “overall” trend because it looks clean and decisive. Yet some of the most expensive analytical mistakes happen when we summarise data
TECH
The Death of Traditional CSS: Rise of Utility-First & AI-Generated StylesThe Death of Traditional CSS: Rise of Utility-First & AI-Generated Styles
For decades, Cascading Style Sheets formed the backbone of web design. Developers relied on carefully structured class hierarchies, large stylesheet files, and naming conventions to manage layouts and visual consistency.
TECH
Min-Max Normalization: Transforming Features to a Fixed Range for Neural Network Input StabilityMin-Max Normalization: Transforming Features to a Fixed Range for Neural Network Input Stability
Introduction Modern machine learning systems, especially neural networks, are highly sensitive to the scale of input data. When features exist on very different numeric ranges, the learning process can become
TECH
Off-Policy Deep Reinforcement Learning with Experience ReplayOff-Policy Deep Reinforcement Learning with Experience Replay
Deep Reinforcement Learning (DRL) has become a powerful framework for training agents to make sequential decisions in complex environments. From game-playing systems to recommendation engines, DRL models learn by interacting
TECH