Create README.md

Author: ananas304

Algorithms and Deep Learning Models/Boxoffice/README.md

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+# Movie Revenue Prediction
+This project aims to predict movie revenue based on various features such as budget, popularity, and runtime using a linear regression model.
+
+## Table of Contents
+- [Installation](#installation)
+- [Dataset](#dataset)
+- [Usage](#usage)
+- [Results](#results)
+
+## Installation
+
+To run this project, you'll need to have Python installed along with the following libraries:
+```requirements.txt
+NumPy
+Pandas
+Matplotlib
+Seaborn
+Scikit-learn
+```
+You can install the necessary libraries using pip:
+
+```bash
+pip install -r requirements.txt
+```
+
+## Dataset
+
+The dataset used in this project is `movie_dataset.csv`, which contains information about various movies, including their budget, revenue, popularity, runtime, and more.
+
+## Usage
+
+1. Clone the repository:
+
+```bash
+git clone <your-repo-url>
+cd <your-repo-directory>
+```
+
+2. Open the Jupyter Notebook:
+
+```bash
+jupyter notebook
+```
+
+3. Run the notebook cells sequentially to load the dataset, preprocess it, and train the linear regression model to make predictions on movie revenue.
+
+## Results
+
+After running the model, you will receive the Mean Absolute Error (MAE) as an evaluation metric to assess the prediction accuracy.