https://github.com/udacity-machinelearning-internship/perceptrons-as-logical-operators
Applying Perceptrons as Logical Operators using Pandas
https://github.com/udacity-machinelearning-internship/perceptrons-as-logical-operators
Last synced: 9 months ago
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Applying Perceptrons as Logical Operators using Pandas
- Host: GitHub
- URL: https://github.com/udacity-machinelearning-internship/perceptrons-as-logical-operators
- Owner: Udacity-MachineLearning-Internship
- Created: 2024-05-15T06:50:04.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-17T03:39:31.000Z (over 1 year ago)
- Last Synced: 2025-01-21T08:24:10.219Z (11 months ago)
- Language: Jupyter Notebook
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README

  [](https://www.python.org/downloads/release/python-380/)
[](https://pypi.org/project/pip/21.0/)

[](https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators/releases/tag/v1.0.0)
[](https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators/graphs/contributors)

This repository contains an implementation of Perceptrons as Logical Operators using Pandas.
## Overview
In this repository, we'll see one of the many great applications of perceptrons. As logical operators! You'll have the chance to create the perceptrons for the most common of these, the AND, OR, and NOT operators. And then, we'll see what to do about the elusive XOR operator. Let's dive in!
## Requirements
To run the code in the Jupyter Notebook, you need to have Python installed on your system along with the following libraries:
- pandas
You can install these libraries using pip:
```bash
pip install pandas
```
## Usage
1. Clone this repository to your local machine:
```bash
git clone https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators.git
```
2. Navigate to the repository directory:
```bash
cd perceptronAsLogicalOperators
```
3. Open and run the Jupyter Notebook `PerceptronAsLogicalOperators.ipynb` using Jupyter Notebook or JupyterLab.
4. Follow along with the code and comments in the notebook to understand how perceptron algorithms as logical operators is implemented using Python.
## Acknowledgements
- [pandas](https://pandas.pydata.org/): The pandas library for data manipulation and analysis in Python.