Machine Learning for C++ developers: DMLLib and VisualDML

Here’s a quick library to write your GPU-based operators and execute them in your Nvidia, AMD, Intel or whatever, along with my new VisualDML tool to design your operators visually. This is a follow ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you’ve ever built a predictive model, worked on a ...
Hosted on MSN

Gradient descent from scratch in Python – step by step tutorial

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. 'SNL' mocks Trump over rising gas prices in cold open ...
IEEE

Gradient Descent Algorithm Based on Extended State Observer for Loss Minimization of Ultralocal Model Predictive Controlled PMSM Drives

Abstract: Hybrid loss minimization algorithms in electrical drives combine the benefits of search-based and model-based approaches to deliver fast and robust dynamic responses. This article presents a ...
GitHub

2.5 LispE vs. Python: A Stochastic Gradient Descent Comparison

This is a question I've been asking myself for years. LispE is not my first programming language - far from it. I have proposed in the past Tamgu - a rather rich language that merges in the same ...
GitHub

2.5 LispE vs. Python: A Stochastic Gradient Descent Comparison

What makes an interpreted language fast? This is a question I've been asking myself for years. LispE is not my first programming language - far from it. I have proposed in the past Tamgu - a rather ...