Box Office Revenue Prediction using Linear Regression Machine learning algorithm

By Devansh Parikh

In this Machine Learning project, we will predict Box office movie revenue using Linear Regression Machine Learning Algorithm.

Dataset Link: cost_revenue_clean.csv

Step-1: Importing Libraries and reading the given data.

import pandas
from pandas import DataFrame
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression

data = pandas.read_csv('cost_revenue_clean.csv')
data.describe()

Step-2: Data Visualization

X = DataFrame(data, columns=['production_budget_usd'])
y = DataFrame(data, columns=['worldwide_gross_usd'])

plt.figure(figsize=(10,6))
plt.scatter(X, y, alpha=0.3)
plt.title('Film Cost vs Global Revenue')
plt.xlabel('Production Budget $')
plt.ylabel('Worldwide Gross $')
plt.ylim(0, 3000000000)
plt.xlim(0, 450000000)
plt.show()

Step-3: Applying Linear Regression Model

regression = LinearRegression()
regression.fit(X, y)

plt.figure(figsize=(10,6))
plt.scatter(X, y, alpha=0.3)

# Adding the regression line here:
plt.plot(X, regression.predict(X), color='red', linewidth=3)

plt.title('Film Cost vs Global Revenue')
plt.xlabel('Production Budget $')
plt.ylabel('Worldwide Gross $')
plt.ylim(0, 3000000000)
plt.xlim(0, 450000000)
plt.show()

Also read:

• Tensorflow Estimator in Python machine learning