Welcome to the Perceptrons Learning Assignment! This assignment is your gateway to understanding one of the fundamental building blocks of artificial neural networks — the perceptron. Whether you're new to the world of machine learning or seeking to reinforce your knowledge, this assignment will provide you with insights into the core concepts of perceptrons.
To begin or resume your assignment, simply copy the repository link and pull it to your local computer (we recommend using virtual studio to edit the files) or click the "Open in GitHub Codespaces" button below. Whether you're a student eager to delve into the world of perceptrons or an enthusiast looking to sharpen your skills, this assignment will guide you through the essential concepts step by step.
Perceptrons are the building blocks of neural networks. They are simple yet powerful models that have paved the way for modern deep learning techniques. This assignment will demystify perceptrons, their architecture, and their role in solving complex problems in various domains.
Throughout this assignment, you will:
- Learn the theory behind perceptrons and how they function.
- Explore practical examples and applications of perceptrons.
- Engage in hands-on exercises to solidify your understanding.
- Have the opportunity to test your knowledge through interactive homework assignments.
This repository contains all the resources you need to complete the assignment successfully. You will be working mostly in the file perceptron_introduction.ipynb, but feel free to poke around the other files as well, you will actually need to look through the source code to answer some of the questions.
We're excited to embark on this learning journey with you as you explore the fascinating world of perceptrons!
Happy learning!