Welcome to M5BMachine 5-Minute Briefing

Understanding ensemble learning from first principles in Excel The post The Machine Learning “Advent Calendar” Day 19: Bagging in Excel appeared first on Towards Data Science....

From a weekend chore to a fun application of valuable operations research principles The post How I Optimized My Leaf Raking Strategy Using Linear Programming appeared first on Towards Data Science....

Understanding forward propagation and backpropagation through explicit formulas The post The Machine Learning “Advent Calendar” Day 18: Neural Network Classifier in Excel appeared first on Towards Data Science....

An optimal solution to the well-known NP-complete problem, when the input values are close enough to each other. The post The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs appeared first on Towards Data Science....

Using Python to generate art The post Generating Artwork in Python Inspired by Hirst’s Million-Dollar Spots Painting appeared first on Towards Data Science....

When indexing hurts more than it helps: how we realized our RAG use case needed a key-value store, not a vector database The post When (Not) to Use Vector DB appeared first on Towards Data Science....

Softmax Regression is simply Logistic Regression extended to multiple classes. By computing one linear score per class and normalizing them with Softmax, we obtain multiclass probabilities without changing the core logic. The loss, the gradients, and the optimization remain the same. Only the number...

In the Author Spotlight series, TDS Editors chat with members of our community about their career path in data science and AI, their writing, and their sources of inspiration. Today, we’re thrilled to share our conversation with Maria Mouschoutzi.  Maria is a Data Analyst and Project Manager with a ...

Learn how to become a more efficient programmer with local testing The post How to Increase Coding Iteration Speed appeared first on Towards Data Science....

This one little trick can bring about enhanced training stability, the use of larger learning rates and improved scaling properties The post NeurIPS 2025 Best Paper Review: Qwen’s Systematic Exploration of Attention Gating appeared first on Towards Data Science....

In this article, we rebuild Logistic Regression step by step directly in Excel. Starting from a binary dataset, we explore why linear regression struggles as a classifier, how the logistic function fixes these issues, and how log-loss naturally appears from the likelihood. With a transparent gradien...

Most breakthroughs in deep learning — from simple neural networks to large language models — are built upon a principle that is much older than AI itself: decentralization. Instead of relying on a powerful “central planner” coordinating and commanding the behaviors of other components, modern deep-l...

Introduction How do we identify latent groups of patients in a large cohort? How can we find similarities among patients that go beyond the well-known comorbidity clusters associated with specific diseases? And more importantly, how can we extract quantitative signals that can be analyzed, compared,...

Linear Regression looks simple, but it introduces the core ideas of modern machine learning: loss functions, optimization, gradients, scaling, and interpretation. In this article, we rebuild Linear Regression in Excel, compare the closed-form solution with Gradient Descent, and see how the coefficie...