Gollapalli Sai Teja·6h agoLinear Regression and Logistic Regression in Machine LearningUnderstand two important supervised machine learning algorithms, how they work, their mathematical concepts, and the differences between…
Krishna Kumar·3d agoDecision Trees Explained Simply: The Complete Machine Learning Guide for BeginnersHave you ever played the game 20 Questions?
T.kiran·4d agoNaive Bayes Algorithm: Understanding the Power of Probability in Machine LearningAn intuitive guide to one of the simplest yet surprisingly powerful classification algorithms in Machine Learning.
Gilaburu·6d agoHow machines learn: Classification, Clustering and BeyondIn our map of AI, ML, deep learning and reinforcement learning we grouped machine learning by the kind of feedback a model gets: right…
Ritesh Rijhwani·Nov 2What Is Machine Learning? The 3 Main Types Explained SimplyA beginner’s guide to supervised, unsupervised, and reinforcement learning — with everyday examples.
Aniruddh·Nov 1Supervised Learning made simpleYou’ve heard “the model learns from data” a hundred times.
Deepak Mehta·Oct 31Broad Categories of Machine-Learning Models: Supervised Learning Models — Part gArticle 2g of 25 — Strengths & ConclusionA response icon1A response icon1
Rinoza jiffry·Oct 30How Netflix Knows You Without Anyone Telling It HowUnsupervised Learning, Part 1: Finding Structure When Nobody Gives You the Answers
NN_Ronin·Oct 28Teaching an AI to Play Chess on Ice (Part 1): Why Curling, and How I Reconstructed Throws from…What if we could see the outcome of a move, but not the action that produced it? I collected shot-by-shot diagrams from Olympic and World…
Medisumeet·Oct 26The Jim Rohn Guide to Machine Learning: Understanding K-Nearest Neighbors (KNN)“You are the average of the five people you spend the most time with.” — Jim RohnA response icon2A response icon2
