Box Office Revenue Prediction using Linear Regression Machine learning algorithm
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()
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