Added Perceptron Network

Perceptron From Scratch/readmd.md

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+Here is a short README file for your Perceptron implementation:
+# Perceptron Implementation
+
+This repository contains a simple implementation of the Perceptron algorithm for binary classification. The Perceptron is a type of linear classifier that updates its weights and bias based on the errors made on the training data.
+
+## Requirements
+
+- numpy
+- pandas
+- matplotlib
+- scikit-learn
+
+You can install these dependencies using pip:
+
+```bash
+pip install numpy pandas matplotlib scikit-learn
+```
+
+## Usage
+
+The `perceptron` class is implemented with methods to fit the model to the training data and make predictions on new data. The dataset used in the example is generated using `make_blobs` from `scikit-learn`.
+
+## Results
+
+The accuracy of the model is printed after training and predicting on the test set. Additionally, a plot is generated to visualize the decision boundary learned by the perceptron.
+
+## How to Use This Repository
+
+- Clone this repository to your local machine.
+
+```bash
+  git clone https://github.com/Niketkumardheeryan/ML-CaPsule/Perceptron From Scratch
+```
+- For Python implementations and visualizations:
+
+1. Ensure you have Jupyter Notebook installed 
+
+```bash
+  pip install jupyter
+```
+2. Navigate to the project directory in your terminal.
+3. Open perceptron.ipynb.