Summary
This context is about an online course that teaches the fundamentals of Artificial Neural Networks (ANNs), a type of artificial intelligence that can learn from data and make predictions or decisions.
Abstract
This course introduction to Neural Networks from Brilliant offers a beginner-friendly exploration of ANNs. It covers various topics such as artificial intelligence, classification, backpropagation, logic gates, convolutional networks, gradient descent, computer vision, activation functions, and universal approximation. The course aims to help learners understand the internal workings of ANNs through hands-on experimentation, without delving into complex mathematics. Basic algebra proficiency and some familiarity with logic concepts are recommended as prerequisites.
Bullet Points
- •Course title: Practice Introduction to Neural Networks
- •Provider: Brilliant
- •Topics covered: Artificial Intelligence, Classification, Backpropagation, Logic Gates, Convolutional Networks, Gradient Descent, Computer Vision, Activation Functions, Universal Approximation
- •Prerequisites: Basic algebra proficiency and familiarity with logic concepts
- •Next course: Quantum Computing (CS & Programming · Level 5)