Beginner-friendly explanation with example math for a simple type of neural network called a perceptron, which has a single binary output. The example uses just a single neuron and three binary inputs. If you've watched other videos but still don't understand the basic building block of a neural network, maybe this will help! Check out written instructions on our website to learn how to do this yourself for a science project:…
Today we’re going to teach John Green Bot how to tell the difference between donuts and bagels using supervised learning! Supervised learning is the process of learning WITH training labels, and is the most widely used kind of learning with it comes to AI - helping with stuff like tagging photos on Facebook and filtering spam from your email. We’re going to start small today and show how just a single neuron (or perceptron) is constructed, and explain the differences between precision and…
This video shows you how to create an AI player to play Tic-Tac-Toe with an unbeatable strategy using the Minimax algorithm on Google Colab. Written instructions and example code are available on the Science Buddies website: https://sciencebuddies.org/science-fair-projects/project-ideas/ArtificialIntelligence_p013/artificial-intelligence/min-max-tic-tac-toe
Science Buddies also hosts a library of instructions for over 1,500 other hands-on science projects, lesson plans, and fun activities for…
This video shows you how to train a K-Nearest Neighbors (KNN) model to predict which passengers survived on the Titanic using machine learning and libraries on Google Colab. Written instructions and example code are available on the Science Buddies website: https://www.sciencebuddies.org/science-fair-projects/project-ideas/ArtificialIntelligence_p009/artificial-intelligence/KNN-titanic-survivor?ytid=9ayEvwmO8GI&ytsrc=description
Science Buddies also hosts a library of instructions for over…
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Welcome back to this series on reinforcement learning! In this video, we'll be introducing the idea of Q-learning with value iteration, which is a reinforcement learning technique used for learning the optimal policy in a Markov Decision Process.
We'll illustrate how this technique works by introducing a game where a reinforcement learning agent tries to maximize points, and through this, we'll also learn…